diff --git a/aws_geo_datasets.json b/aws_geo_datasets.json index 5f14044..a125c20 100644 --- a/aws_geo_datasets.json +++ b/aws_geo_datasets.json @@ -5312,9 +5312,9 @@ { "Name": "Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (af-south-1 region)", "Description": "GBIF species occurrence data in Parquet format (af-south-1 region)", - "ARN": "arn:aws:sns:af-south-1:288719126026:gbif-open-data-af-south-1-object_created", + "ARN": "arn:aws:s3:::gbif-open-data-af-south-1", "Region": "af-south-1", - "Type": "SNS Topic", + "Type": "S3 Bucket", "Documentation": "Documentation can be found [here](https://github.com/gbif/occurrence/blob/master/aws-public-data.md). You can learn more about GBIF [here](https://www.gbif.org).", "Contact": "helpdesk@gbif.org", "ManagedBy": "The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org))", @@ -5329,16 +5329,18 @@ "life sciences" ], "RequesterPays": null, - "Explore": null, + "Explore": [ + "[Browse bucket](https://gbif-open-data-af-south-1.s3.af-south-1.amazonaws.com/index.html)" + ], "Host": null, "AccountRequired": null }, { "Name": "Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (af-south-1 region)", "Description": "GBIF species occurrence data in Parquet format (af-south-1 region)", - "ARN": "arn:aws:s3:::gbif-open-data-af-south-1", + "ARN": "arn:aws:sns:af-south-1:288719126026:gbif-open-data-af-south-1-object_created", "Region": "af-south-1", - "Type": "S3 Bucket", + "Type": "SNS Topic", "Documentation": "Documentation can be found [here](https://github.com/gbif/occurrence/blob/master/aws-public-data.md). You can learn more about GBIF [here](https://www.gbif.org).", "Contact": "helpdesk@gbif.org", "ManagedBy": "The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org))", @@ -5353,9 +5355,7 @@ "life sciences" ], "RequesterPays": null, - "Explore": [ - "[Browse bucket](https://gbif-open-data-af-south-1.s3.af-south-1.amazonaws.com/index.html)" - ], + "Explore": null, "Host": null, "AccountRequired": null }, @@ -6155,7 +6155,7 @@ "ARN": "arn:aws:s3:::gisimageryingov", "Region": "us-east-2", "Type": "S3 Bucket", - "Documentation": "https://imagery-ingov.hub.arcgis.com/", + "Documentation": "https://imagery.gio.in.gov/", "Contact": "sscholer@iot.in.gov", "ManagedBy": "Indiana Geographic Information Office", "UpdateFrequency": "The State of Indiana has had a 4-year cycle collecting imagery. The collections are designated by counties in three groups that cover Indiana, South to North. These areas are frequently referred to as Tiers in the other documentation. For example, tier 1 (Central 3rd) extends from Harrison County in the South to Elkhart and St. Joseph County in the North, while Tier 2 consists of the counties to the eastern side of the State, and Tier 3 is those counties to the western side of the State.", @@ -6177,6 +6177,33 @@ "Host": null, "AccountRequired": null }, + { + "Name": "Indiana Statewide Elevation Catalog", + "Description": "State of Indiana Elevation archive", + "ARN": "arn:aws:s3:::giselevationingov", + "Region": "us-east-2", + "Type": "S3 Bucket", + "Documentation": "https://elevation.gio.in.gov/", + "Contact": "sscholer@iot.in.gov", + "ManagedBy": "Indiana Geographic Information Office", + "UpdateFrequency": "The State of Indiana has another four-year cycle of collecting orthoimagery and Lidar starting in 2025 and continuing through 2028. The collections are designated by counties in three groups that cover Indiana, South to North. These areas are frequently referred to as Tiers in the other documentation. For example, tier 1 (Central 3rd) extends from Harrison County in the South to Elkhart and St. Joseph County in the North, while Tier 2 consists of the counties to the eastern side of the State, and Tier 3 is those counties to the western side of the State.", + "License": "Access to Indiana Geographic Information Office Lidar is governed by Creative Commons 0 (CC0): https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "Tags": [ + "lidar", + "aws-pds", + "earth observation", + "geospatial", + "imaging", + "mapping", + "natural resource", + "sustainability", + "agriculture" + ], + "RequesterPays": null, + "Explore": null, + "Host": null, + "AccountRequired": null + }, { "Name": "Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) - ITS_LIVE Data S3 Bucket", "Description": "ITS_LIVE Data S3 Bucket", @@ -11039,7 +11066,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewSNPPObject", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA21Object", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -11062,7 +11089,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA20Object", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewSNPPObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -11085,7 +11112,7 @@ { "Name": "NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed", "Description": "New data notifications for JPSS data, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA21Object", + "ARN": "arn:aws:sns:us-east-1:709902155096:NewNOAA20Object", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS", @@ -12417,7 +12444,7 @@ { "Name": "NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", "Description": "New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject", + "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00332", @@ -12440,7 +12467,7 @@ { "Name": "NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", "Description": "New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowed", - "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject", + "ARN": "arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject", "Region": "us-east-1", "Type": "SNS Topic", "Documentation": "https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00332", diff --git a/aws_geo_datasets.tsv b/aws_geo_datasets.tsv index 7c98629..b2c768b 100644 --- a/aws_geo_datasets.tsv +++ b/aws_geo_datasets.tsv @@ -192,8 +192,8 @@ GEOS-Chem Nested Input Data Top-level directory for all GEOS-Chem nested-grid da Geosnap Data, Center for Geospatial Sciences Data files stored as Apache parquet and GeoTiff in a public bucket arn:aws:s3:::spatial-ucr us-east-1 S3 Bucket https://spatialucr.github.io/geosnap-guide/content/home Eli Knaap [UCR Center for Geospatial Sciences](https://spatial.ucr.edu) Annually BSD aws-pds, urban, geospatial, demographics Global 30m Height Above Nearest Drainage (HAND) - GLO-30 HAND S3 bucket GLO-30 HAND S3 bucket arn:aws:s3:::glo-30-hand us-west-2 S3 Bucket https://glo-30-hand.s3.us-west-2.amazonaws.com/readme.html https://asf.alaska.edu/asf/contact-us/ [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) None, except HAND may be updated if the[ Copernicus GLO-30 Public](https://regis Copyright 2022 Alaska Satellite Facility (ASF). Produced using the Copernicus Wo aws-pds, elevation, hydrology, agriculture, disaster response, satellite imagery, geospatial, cog, stac ['[STAC V1.0.0 endpoint](https://stac.asf.alaska.edu/collections/glo-30-hand)', '[Via STAC Browser](https://radiantearth.github.io/stac-browser/#/external/stac.asf.alaska.edu/collections/glo-30-hand)'] Global 30m Height Above Nearest Drainage (HAND) - Notifications for new data Notifications for new data arn:aws:sns:us-west-2:879002409890:glo-30-hand-object_created us-west-2 SNS Topic https://glo-30-hand.s3.us-west-2.amazonaws.com/readme.html https://asf.alaska.edu/asf/contact-us/ [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) None, except HAND may be updated if the[ Copernicus GLO-30 Public](https://regis Copyright 2022 Alaska Satellite Facility (ASF). Produced using the Copernicus Wo aws-pds, elevation, hydrology, agriculture, disaster response, satellite imagery, geospatial, cog, stac -Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (af-south-1 region) GBIF species occurrence data in Parquet format (af-south-1 region) arn:aws:sns:af-south-1:288719126026:gbif-open-data-af-south-1-object_created af-south-1 SNS Topic Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (af-south-1 region) GBIF species occurrence data in Parquet format (af-south-1 region) arn:aws:s3:::gbif-open-data-af-south-1 af-south-1 S3 Bucket Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences ['[Browse bucket](https://gbif-open-data-af-south-1.s3.af-south-1.amazonaws.com/index.html)'] +Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (af-south-1 region) GBIF species occurrence data in Parquet format (af-south-1 region) arn:aws:sns:af-south-1:288719126026:gbif-open-data-af-south-1-object_created af-south-1 SNS Topic Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (ap-southeast-2 region) GBIF species occurrence data in Parquet format (ap-southeast-2 region) arn:aws:s3:::gbif-open-data-ap-southeast-2 ap-southeast-2 S3 Bucket Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences ['[Browse bucket](https://gbif-open-data-ap-southeast-2.s3.ap-southeast-2.amazonaws.com/index.html)'] Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (ap-southeast-2 region) GBIF species occurrence data in Parquet format (ap-southeast-2 region) arn:aws:sns:af-south-1:288719126026:gbif-open-data-ap-southeast-2-object_created ap-southeast-2 SNS Topic Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences Global Biodiversity Information Facility (GBIF) Species Occurrences - GBIF species occurrence data in Parquet format (eu-central-1 region) GBIF species occurrence data in Parquet format (eu-central-1 region) arn:aws:sns:af-south-1:288719126026:gbif-open-data-eu-central-1-object_created eu-central-1 SNS Topic Documentation can be found [here](https://github.com/gbif/occurrence/blob/master helpdesk@gbif.org The Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) Snapshots of GBIF are taken on a monthly basis [CC-BY-NC](https://creativecommons.org/licenses/by-nc/4.0/) under the GBIF [term aws-pds, earth observation, biodiversity, bioinformatics, conservation, life sciences @@ -224,7 +224,8 @@ High resolution, annual cropland and landcover maps for selected African countri Homeland Security and Infrastructure US Cities A Requester Pays Bucket of HSIP data including building footprints, LiDAR, ortho arn:aws:s3:::usgs-lidar-uscities us-west-2 S3 Bucket https://github.com/hobuinc/hsip-lidar https://github.com/hobuinc/hsip-lidar [Hobu, Inc.](https://hobu.co) Periodically US Government Public Domain https://www.usgs.gov/faqs/what-are-terms-uselicensin aws-pds, elevation, disaster response, geospatial, lidar True IDEAM - Colombian Radar Network Level II data arn:aws:s3:::s3-radaresideam us-east-1 S3 Bucket http://www.pronosticosyalertas.gov.co/archivos-radar atencionalciudadano@ideam.gov.co, radares_ideam@ideam.gov.co [IDEAM](http://www.ideam.gov.co/) Updated level II data is added as soon as it is available. Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, agriculture, earth observation, natural resource, weather, meteorological ISERV ISERV Optical Imagery arn:aws:s3:::nasa-iserv us-west-2 S3 Bucket https://stacindex.org/collections/nasa-iserv support@radiant.earth [Radiant Earth Foundation](https://www.radiant.earth/) Not updated The data is released under a ODC Public Domain Dedication & License 1.0 ([PDDL-1 aws-pds, geospatial, earth observation, satellite imagery, environmental -Indiana Statewide Digital Aerial Imagery Catalog State of Indiana digital orthophotography archive arn:aws:s3:::gisimageryingov us-east-2 S3 Bucket https://imagery-ingov.hub.arcgis.com/ sscholer@iot.in.gov Indiana Geographic Information Office The State of Indiana has had a 4-year cycle collecting imagery. The collections Access to Indiana Geographic Information Office Orthoimagery is governed by Crea aerial imagery, aws-pds, earth observation, geospatial, imaging, mapping, cog, natural resource, sustainability, agriculture +Indiana Statewide Digital Aerial Imagery Catalog State of Indiana digital orthophotography archive arn:aws:s3:::gisimageryingov us-east-2 S3 Bucket https://imagery.gio.in.gov/ sscholer@iot.in.gov Indiana Geographic Information Office The State of Indiana has had a 4-year cycle collecting imagery. The collections Access to Indiana Geographic Information Office Orthoimagery is governed by Crea aerial imagery, aws-pds, earth observation, geospatial, imaging, mapping, cog, natural resource, sustainability, agriculture +Indiana Statewide Elevation Catalog State of Indiana Elevation archive arn:aws:s3:::giselevationingov us-east-2 S3 Bucket https://elevation.gio.in.gov/ sscholer@iot.in.gov Indiana Geographic Information Office The State of Indiana has another four-year cycle of collecting orthoimagery and Access to Indiana Geographic Information Office Lidar is governed by Creative Co lidar, aws-pds, earth observation, geospatial, imaging, mapping, natural resource, sustainability, agriculture Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) - ITS_LIVE Data S3 Bucket ITS_LIVE Data S3 Bucket arn:aws:s3:::its-live-data us-west-2 S3 Bucket https://its-live-data.s3.us-west-2.amazonaws.com/README.html If you have questions about the data itself or the processing methods used, plea [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Up to daily, as new satellite imagery is made available. [Creative Commons Zero (CC0) 1.0 Universal License](https://creativecommons.org/ aws-pds, ice, earth observation, satellite imagery, geophysics, geospatial, global, cog, netcdf, zarr, stac ['[Browse Bucket](https://its-live-data.s3.amazonaws.com/index.html)'] Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) - Notifications for new data Notifications for new data arn:aws:sns:us-west-2:367587189974:its-live-data-object_created us-west-2 SNS Topic https://its-live-data.s3.us-west-2.amazonaws.com/README.html If you have questions about the data itself or the processing methods used, plea [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Up to daily, as new satellite imagery is made available. [Creative Commons Zero (CC0) 1.0 Universal License](https://creativecommons.org/ aws-pds, ice, earth observation, satellite imagery, geophysics, geospatial, global, cog, netcdf, zarr, stac JAXA / USGS / NASA Kaguya/SELENE Terrain Camera Observations - Scenes and metadata for monoscopic observing mode Scenes and metadata for monoscopic observing mode arn:aws:s3:::astrogeo-ard/moon/kaguya/terrain_camera/monoscopic/uncontrolled/ us-west-2 S3 Bucket https://stac.astrogeology.usgs.gov/docs/data/moon/kaguyatc/ https://answers.usgs.gov/ [NASA](https://www.nasa.gov) The Kaguya/SELENE mission has completed. No updates to this dataset are planned. [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) aws-pds, planetary, satellite imagery, stac, cog ['[STAC Catalog](https://stac.astrogeology.usgs.gov/browser-dev/#/api/collections/kaguya_terrain_camera_monoscopic_uncontrolled_observations)'] @@ -408,9 +409,9 @@ NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS NOAA-20 Data NOAA JPSS NOAA NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS NOAA-21 Data NOAA JPSS NOAA-21 Data arn:aws:s3:::noaa-nesdis-n21-pds us-east-1 S3 Bucket https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nesdis-n21-pds.s3.amazonaws.com/index.html)'] NOAA Joint Polar Satellite System (JPSS) - NOAA JPSS SNPP (Suomi NPP) Data NOAA JPSS SNPP (Suomi NPP) Data arn:aws:s3:::noaa-nesdis-snpp-pds us-east-1 S3 Bucket https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nesdis-snpp-pds.s3.amazonaws.com/index.html)'] NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewJPSSObject us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather +NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA21Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewSNPPObject us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA20Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather -NOAA Joint Polar Satellite System (JPSS) - New data notifications for JPSS data, only Lambda and SQS protocols allowed New data notifications for JPSS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:709902155096:NewNOAA21Object us-east-1 SNS Topic https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/JPSS For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) New data is added as soon as it's available Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Multi-Radar/Multi-Sensor System (MRMS) - NOAA Multi-Radar/Multi-Sensor System (MRMS) NOAA Multi-Radar/Multi-Sensor System (MRMS) arn:aws:s3:::noaa-mrms-pds us-east-1 S3 Bucket https://www.nssl.noaa.gov/projects/mrms/ For specific MRMS data questions, please reach out to the MRMS Team at mrms@noaa [NOAA](http://www.noaa.gov/) Data is delivered in real-time with a 2-minute update cycle. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-mrms-pds.s3.amazonaws.com/index.html)'] NOAA Multi-Radar/Multi-Sensor System (MRMS) - New data notifications for MRMS data, only Lambda and SQS protocols allowed New data notifications for MRMS data, only Lambda and SQS protocols allowed arn:aws:sns:us-east-1:123901341784:NewMRMSObject us-east-1 SNS Topic https://www.nssl.noaa.gov/projects/mrms/ For specific MRMS data questions, please reach out to the MRMS Team at mrms@noaa [NOAA](http://www.noaa.gov/) Data is delivered in real-time with a 2-minute update cycle. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) Multi-Year Reanalysis of Remotely Sensed Storms arn:aws:s3:::noaa-oar-myrorss-pds us-east-1 S3 Bucket https://osf.io/9gzp2/ For any data delivery issues or any questions in general, please contact the NOA [NOAA](http://www.noaa.gov/) No updates Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, earth observation, meteorological, natural resource, sustainability, weather ['[Browse Bucket](https://noaa-oar-myrorss-pds.s3.amazonaws.com/index.html)'] @@ -462,8 +463,8 @@ NOAA Terrestrial Climate Data Records - NDVI NDVI arn:aws:s3:::noaa-cdr-ndvi-pds NOAA Terrestrial Climate Data Records - Snow Cover Extent Snow Cover Extent arn:aws:s3:::noaa-cdr-snow-cover-ext-north-pds us-east-1 S3 Bucket https://www.ncdc.noaa.gov/cdr For questions regarding the specific CDR data holdings, please contact NCEI.SAT. [NOAA](http://www.noaa.gov/) Climate Data Records are updated independently. For update frequency for a speci Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, sustainability, weather ['[Browse Bucket](https://noaa-cdr-snow-cover-ext-north-pds.s3.amazonaws.com/index.html)'] NOAA U.S. Climate Gridded Dataset (NClimGrid) - Daily NClimGrid Data Daily NClimGrid Data arn:aws:s3:::noaa-nclimgrid-daily-pds us-east-1 S3 Bucket https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nclimgrid-daily-pds.s3.amazonaws.com/index.html)'] NOAA U.S. Climate Gridded Dataset (NClimGrid) - Monthly NClimGrid Data Monthly NClimGrid Data arn:aws:s3:::noaa-nclimgrid-monthly-pds us-east-1 S3 Bucket https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-nclimgrid-monthly-pds.s3.amazonaws.com/index.html)'] -NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridMonthlyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather +NOAA U.S. Climate Gridded Dataset (NClimGrid) - New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe New data notifications for Daily NClimGrid, only Lambda and SQS protocols allowe arn:aws:sns:us-east-1:123901341784:NewNClimGridDailyObject us-east-1 SNS Topic https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc: For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Monthly Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA U.S. Climate Normals US Climate Normals Data arn:aws:s3:::noaa-normals-pds us-east-1 S3 Bucket [https://www.ncei.noaa.gov/products/us-climate-normals](https://www.ncei.noaa.go For any questions regarding data delivery or any general questions regarding the [NOAA](http://www.noaa.gov/) Data is updated on 10 year cycles or when corrections are implemented. Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, sustainability, weather ['[Browse Bucket](https://noaa-normals-pds.s3.amazonaws.com/index.html)'] NOAA Unified Forecast System (UFS) Global Ensemble Forecast System (GEFS) Version 13 Replay - New data notifications for UFS / GEFS Replay Data, only Lambda and SQS protocols New data notifications for UFS / GEFS Replay Data, only Lambda and SQS protocols arn:aws:sns:us-east-1:123901341784:NewUFS-GEFSObject us-east-1 SNS Topic https://psl.noaa.gov/data/ufs_replay/ For questions regarding data content or quality, visit [the NOAA GEFS Replay sit [NOAA](http://www.noaa.gov/) Static Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather NOAA Unified Forecast System (UFS) Global Ensemble Forecast System (GEFS) Version 13 Replay - UFS / GEFS Replay Data UFS / GEFS Replay Data arn:aws:s3:::-noaa-ufs-gefsv13replay-pds us-east-1 S3 Bucket https://psl.noaa.gov/data/ufs_replay/ For questions regarding data content or quality, visit [the NOAA GEFS Replay sit [NOAA](http://www.noaa.gov/) Static Open Data. There are no restrictions on the use of this data. aws-pds, agriculture, climate, meteorological, weather ['[Browse Bucket](https://noaa-ufs-gefsv13replay-pds.s3.amazonaws.com/index.html)'] diff --git a/aws_open_datasets.json b/aws_open_datasets.json index 7976e1c..809cb65 100644 --- a/aws_open_datasets.json +++ b/aws_open_datasets.json @@ -12428,7 +12428,7 @@ "ARN": "arn:aws:s3:::gisimageryingov", "Region": "us-east-2", "Type": "S3 Bucket", - "Documentation": "https://imagery-ingov.hub.arcgis.com/", + "Documentation": "https://imagery.gio.in.gov/", "Contact": "sscholer@iot.in.gov", "ManagedBy": "Indiana Geographic Information Office", "UpdateFrequency": "The State of Indiana has had a 4-year cycle collecting imagery. The collections are designated by counties in three groups that cover Indiana, South to North. These areas are frequently referred to as Tiers in the other documentation. For example, tier 1 (Central 3rd) extends from Harrison County in the South to Elkhart and St. Joseph County in the North, while Tier 2 consists of the counties to the eastern side of the State, and Tier 3 is those counties to the western side of the State.", diff --git a/aws_open_datasets.tsv b/aws_open_datasets.tsv index d064e6f..4f93bd3 100644 --- a/aws_open_datasets.tsv +++ b/aws_open_datasets.tsv @@ -444,7 +444,7 @@ Image classification - fast.ai datasets Datasets arn:aws:s3:::fast-ai-imageclas Image localization - fast.ai datasets Datasets arn:aws:s3:::fast-ai-imagelocal us-east-1 S3 Bucket http://course.fast.ai/datasets info@fast.ai [fast.ai](http://www.fast.ai/) As required Varies by dataset - see documentation link aws-pds, deep learning, computer vision, machine learning InRad COVID-19 X-Ray and CT Scans Radiographs in png format CT-Scans in nii format Object names include a hash arn:aws:s3:::inlab-opendata-covid-anonymized-images us-west-2 S3 Bucket https://docs.google.com/document/d/1isuyQnszSio3JUZ1_3C4DTPC1fvaJGAR4ziTWGRi8K4/ inlab.inrad@hc.fm.usp.br [Faculdade de Medicina da Universidade de São Paulo Institute of Radiology (InRa As Necessary Creative Commons Attribution 4.0 International (CC BY 4.0) aws-pds, bioinformatics, coronavirus, COVID-19, health, life sciences, medicine, SARS Indexes for Kaiju This AWS S3 bucket contains pre-built indexes for Kaiju arn:aws:s3:::kaiju-idx eu-central-1 S3 Bucket https://bioinformatics-centre.github.io/kaiju/downloads.html https://github.com/bioinformatics-centre/kaiju/issues [Peter Menzel](https://github.com/pmenzel) roughly yearly Public Domain aws-pds, bioinformatics, biology, genomic, life sciences, whole genome sequencing, reference index, metagenomics, microbiome -Indiana Statewide Digital Aerial Imagery Catalog State of Indiana digital orthophotography archive arn:aws:s3:::gisimageryingov us-east-2 S3 Bucket https://imagery-ingov.hub.arcgis.com/ sscholer@iot.in.gov Indiana Geographic Information Office The State of Indiana has had a 4-year cycle collecting imagery. The collections Access to Indiana Geographic Information Office Orthoimagery is governed by Crea aerial imagery, aws-pds, earth observation, geospatial, imaging, mapping, cog, natural resource, sustainability, agriculture +Indiana Statewide Digital Aerial Imagery Catalog State of Indiana digital orthophotography archive arn:aws:s3:::gisimageryingov us-east-2 S3 Bucket https://imagery.gio.in.gov/ sscholer@iot.in.gov Indiana Geographic Information Office The State of Indiana has had a 4-year cycle collecting imagery. The collections Access to Indiana Geographic Information Office Orthoimagery is governed by Crea aerial imagery, aws-pds, earth observation, geospatial, imaging, mapping, cog, natural resource, sustainability, agriculture Integrative Analysis of Lung Adenocarcinoma in Environment and Genetics Lung cancer Etiology (Phase 2) Whole Genome Sequencing, Whole Exome Sequencing arn:aws:s3:::gdc-cddp-eagle-1-phs001239-2-open us-east-1 S3 Bucket https://ftp.ncbi.nlm.nih.gov/dbgap/studies/phs001239/phs001239.v1.p1 support@nci-gdc.datacommons.io [Center for Translational Data Science at The University of Chicago](https://ctd Genomic Data Commons (GDC) is source of truth for this dataset; GDC offers month (NIH Genomic Data Sharing Policy)[https://gdc.cancer.gov/access-data/data-access cancer, whole exome sequencing, whole genome sequencing, aws-pds, life sciences, STRIDES, genomic, epigenomics Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) ITS_LIVE Data S3 Bucket arn:aws:s3:::its-live-data us-west-2 S3 Bucket https://its-live-data.s3.us-west-2.amazonaws.com/README.html If you have questions about the data itself or the processing methods used, plea [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Up to daily, as new satellite imagery is made available. [Creative Commons Zero (CC0) 1.0 Universal License](https://creativecommons.org/ aws-pds, ice, earth observation, satellite imagery, geophysics, geospatial, global, cog, netcdf, zarr, stac ['[Browse Bucket](https://its-live-data.s3.amazonaws.com/index.html)'] Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) Notifications for new data arn:aws:sns:us-west-2:367587189974:its-live-data-object_created us-west-2 SNS Topic https://its-live-data.s3.us-west-2.amazonaws.com/README.html If you have questions about the data itself or the processing methods used, plea [The Alaska Satellite Facility (ASF)](https://asf.alaska.edu/) Up to daily, as new satellite imagery is made available. [Creative Commons Zero (CC0) 1.0 Universal License](https://creativecommons.org/ aws-pds, ice, earth observation, satellite imagery, geophysics, geospatial, global, cog, netcdf, zarr, stac diff --git a/gee_catalog.json b/gee_catalog.json index 6e05c4d..dd69c50 100644 --- a/gee_catalog.json +++ b/gee_catalog.json @@ -114,7 +114,7 @@ "snippet": "ee.ImageCollection('ASTER/AST_L1T_003')", "provider": "NASA LP DAAC at the USGS EROS Center", "state_date": "2000-03-04", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir", @@ -726,7 +726,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S1_GRD')", "provider": "European Union/ESA/Copernicus", "state_date": "2014-10-03", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel", @@ -744,7 +744,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-27", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -56, 180, 83", "deprecated": true, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -762,7 +762,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY')", "provider": "European Union/ESA/Copernicus/SentinelHub", "state_date": "2015-06-27", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub", @@ -780,7 +780,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2015-06-27", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, radiance, sentinel", @@ -798,7 +798,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -56, 180, 83", "deprecated": true, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -816,7 +816,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')", "provider": "European Union/ESA/Copernicus", "state_date": "2017-03-28", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -56, 180, 83", "deprecated": false, "keywords": "copernicus, esa, eu, msi, reflectance, sentinel, sr", @@ -834,7 +834,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S3/OLCI')", "provider": "European Union/ESA/Copernicus", "state_date": "2016-10-18", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "copernicus, esa, eu, olci, radiance, sentinel, toa", @@ -852,7 +852,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -870,7 +870,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai", @@ -888,7 +888,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-05", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi", @@ -906,7 +906,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-11-22", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi", @@ -924,7 +924,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-10-02", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -942,7 +942,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -960,7 +960,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -978,7 +978,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -1086,7 +1086,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2024-11-07", + "end_date": "2024-11-08", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi", @@ -1104,7 +1104,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-06-28", - "end_date": "2024-11-02", + "end_date": "2024-11-03", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi", @@ -1122,7 +1122,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-09-08", - "end_date": "2024-11-07", + "end_date": "2024-11-08", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -1140,7 +1140,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-04-30", - "end_date": "2024-10-27", + "end_date": "2024-10-28", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi", @@ -1158,7 +1158,7 @@ "snippet": "ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2')", "provider": "European Union/ESA/Copernicus", "state_date": "2018-12-05", - "end_date": "2024-11-07", + "end_date": "2024-11-08", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi", @@ -1572,7 +1572,7 @@ "snippet": "ee.ImageCollection('ECMWF/CAMS/NRT')", "provider": "European Centre for Medium-Range Weather Forecasts (ECMWF)", "state_date": "2016-06-22", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter", @@ -1626,7 +1626,7 @@ "snippet": "ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR')", "provider": "Daily Aggregates: Google and Copernicus Climate Data Store", "state_date": "1950-01-02", - "end_date": "2024-11-03", + "end_date": "2024-11-05", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind", @@ -1644,7 +1644,7 @@ "snippet": "ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY')", "provider": "Copernicus Climate Data Store", "state_date": "1950-01-01", - "end_date": "2024-11-05", + "end_date": "2024-11-06", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind", @@ -2400,7 +2400,7 @@ "snippet": "ee.ImageCollection('FIRMS')", "provider": "NASA / LANCE / EOSDIS", "state_date": "2000-11-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal", @@ -2688,7 +2688,7 @@ "snippet": "ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED')", "provider": "Google Earth Engine", "state_date": "2015-06-27", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "google, cloud, sentinel2_derived", @@ -2706,7 +2706,7 @@ "snippet": "ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1')", "provider": "World Resources Institute", "state_date": "2015-06-27", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "global, google, landcover, landuse, nrt, sentinel2_derived", @@ -2994,7 +2994,7 @@ "snippet": "ee.ImageCollection('IDAHO_EPSCOR/GRIDMET')", "provider": "University of California Merced", "state_date": "1979-01-01", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-124.9, 24.9, -66.8, 49.6", "deprecated": false, "keywords": "climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind", @@ -3750,7 +3750,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index", @@ -3804,7 +3804,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst", @@ -3858,7 +3858,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color", @@ -3912,7 +3912,7 @@ "snippet": "ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3')", "provider": "Global Change Observation Mission (GCOM)", "state_date": "2021-11-29", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst", @@ -3930,7 +3930,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "2014-03-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -3966,7 +3966,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "2014-03-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -3984,7 +3984,7 @@ "snippet": "ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational')", "provider": "JAXA Earth Observation Research Center", "state_date": "1998-01-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -60, 180, 60", "deprecated": false, "keywords": "climate, geophysical, gpm, hourly, jaxa, precipitation, weather", @@ -5496,7 +5496,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC08/C02/T1_RT')", "provider": "USGS", "state_date": "2013-03-18", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs", @@ -5514,7 +5514,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA')", "provider": "USGS/Google", "state_date": "2013-03-18", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l8, landsat, lc8, toa, usgs", @@ -5604,7 +5604,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1')", "provider": "USGS", "state_date": "2021-10-31", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs", @@ -5640,7 +5640,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA')", "provider": "USGS/Google", "state_date": "2021-10-31", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, landsat, toa, usgs", @@ -5658,7 +5658,7 @@ "snippet": "ee.ImageCollection('LANDSAT/LC09/C02/T2')", "provider": "USGS", "state_date": "2021-11-02", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs", @@ -9690,7 +9690,7 @@ "snippet": "ee.ImageCollection('NASA/EMIT/L1B/RAD')", "provider": "NASA Jet Propulsion Laboratory", "state_date": "2022-08-09", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emit, nasa, radiance", @@ -9708,7 +9708,7 @@ "snippet": "ee.ImageCollection('NASA/EMIT/L2A/RFL')", "provider": "NASA Jet Propulsion Laboratory", "state_date": "2022-08-09", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, emit, nasa, reflectance", @@ -9798,7 +9798,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf')", "provider": "NASA / GMAO", "state_date": "2022-10-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9816,7 +9816,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr')", "provider": "NASA / GMAO", "state_date": "2022-10-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9834,7 +9834,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf')", "provider": "NASA / GMAO", "state_date": "2018-01-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9852,7 +9852,7 @@ "snippet": "ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr')", "provider": "NASA / GMAO", "state_date": "2018-01-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "composition, forecast, geos, gmao, nasa", @@ -9996,7 +9996,7 @@ "snippet": "ee.ImageCollection('NASA/GPM_L3/IMERG_V07')", "provider": "NASA GES DISC at NASA Goddard Space Flight Center", "state_date": "2000-06-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, geophysical, gpm, half_hourly, imerg, jaxa, nasa, precipitation, weather", @@ -10320,7 +10320,7 @@ "snippet": "ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2')", "provider": "NASA / LANCE / NOAA20_VIIRS", "state_date": "2023-10-08", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs", @@ -10338,7 +10338,7 @@ "snippet": "ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2')", "provider": "NASA / LANCE / SNPP_VIIRS", "state_date": "2023-09-03", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs", @@ -10446,7 +10446,7 @@ "snippet": "ee.ImageCollection('NASA/NLDAS/FORA0125_H002')", "provider": "NASA GES DISC at NASA Goddard Space Flight Center", "state_date": "1979-01-01", - "end_date": "2024-11-08", + "end_date": "2024-11-09", "bbox": "-125.15, 24.85, -66.85, 53.28", "deprecated": false, "keywords": "climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind", @@ -10608,7 +10608,7 @@ "snippet": "ee.ImageCollection('NASA/SMAP/SPL3SMP_E/006')", "provider": "Google and NSIDC", "state_date": "2023-12-04", - "end_date": "2024-11-09", + "end_date": "2024-11-11", "bbox": "-180, -84, 180, 84", "deprecated": false, "keywords": "drought, nasa, smap, soil_moisture, surface, weather", @@ -10626,7 +10626,7 @@ "snippet": "ee.ImageCollection('NASA/SMAP/SPL4SMGP/007')", "provider": "Google and NSIDC", "state_date": "2015-03-31", - "end_date": "2024-11-06", + "end_date": "2024-11-10", "bbox": "-180, -84, 180, 84", "deprecated": false, "keywords": "drought, nasa, smap, soil_moisture, surface, weather", @@ -10824,7 +10824,7 @@ "snippet": "ee.ImageCollection('NCEP_RE/sea_level_pressure')", "provider": "NCEP", "state_date": "1948-01-01", - "end_date": "2024-11-08", + "end_date": "2024-11-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, climate, geophysical, ncep, noaa, pressure, reanalysis", @@ -10842,7 +10842,7 @@ "snippet": "ee.ImageCollection('NCEP_RE/surface_temp')", "provider": "NCEP", "state_date": "1948-01-01", - "end_date": "2024-11-08", + "end_date": "2024-11-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature", @@ -10860,7 +10860,7 @@ "snippet": "ee.ImageCollection('NCEP_RE/surface_wv')", "provider": "NCEP", "state_date": "1948-01-01", - "end_date": "2024-11-08", + "end_date": "2024-11-09", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, climate, geophysical, ncep, noaa, precipitable, reanalysis, vapor", @@ -11094,7 +11094,7 @@ "snippet": "ee.ImageCollection('NOAA/CDR/OISST/V2_1')", "provider": "NOAA", "state_date": "1981-09-01", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature", @@ -11166,7 +11166,7 @@ "snippet": "ee.ImageCollection('NOAA/CFSR')", "provider": "NOAA NWS National Centers for Environmental Prediction (NCEP)", "state_date": "2018-12-13", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather", @@ -11202,7 +11202,7 @@ "snippet": "ee.ImageCollection('NOAA/CPC/Precipitation')", "provider": "NOAA Physical Sciences Laboratory", "state_date": "2006-01-01", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, noaa, precipitation, weather", @@ -11220,7 +11220,7 @@ "snippet": "ee.ImageCollection('NOAA/CPC/Temperature')", "provider": "NOAA Physical Sciences Laboratory", "state_date": "1979-01-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "daily, noaa, precipitation, weather", @@ -11274,7 +11274,7 @@ "snippet": "ee.ImageCollection('NOAA/GFS0P25')", "provider": "NOAA/NCEP/EMC", "state_date": "2015-07-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind", @@ -11292,7 +11292,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCC')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -11310,7 +11310,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/FDCF')", "provider": "NOAA", "state_date": "2017-05-24", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire", @@ -11328,7 +11328,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPC')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-152.11, 14, -49.18, 56.77", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11346,7 +11346,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPF')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11364,7 +11364,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/16/MCMIPM')", "provider": "NOAA", "state_date": "2017-07-10", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather", @@ -11472,7 +11472,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCC')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -11490,7 +11490,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/FDCF')", "provider": "NOAA", "state_date": "2022-10-13", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire", @@ -11508,7 +11508,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPC')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, 14.57, 180, 53.51", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11526,7 +11526,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPF')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11544,7 +11544,7 @@ "snippet": "ee.ImageCollection('NOAA/GOES/18/MCMIPM')", "provider": "NOAA", "state_date": "2018-12-04", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather", @@ -11652,7 +11652,7 @@ "snippet": "ee.ImageCollection('NOAA/NWS/RTMA')", "provider": "NOAA/NWS", "state_date": "2011-01-01", - "end_date": "2024-11-11", + "end_date": "2024-11-12", "bbox": "-130.17, 20.15, -60.81, 52.91", "deprecated": false, "keywords": "climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind", @@ -11886,7 +11886,7 @@ "snippet": "ee.ImageCollection('NOAA/VIIRS/001/VNP46A2')", "provider": "NASA LAADS DAAC", "state_date": "2012-01-19", - "end_date": "2024-10-26", + "end_date": "2024-10-27", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "brdf, daily, nasa, noaa, viirs", @@ -12030,7 +12030,7 @@ "snippet": "ee.ImageCollection('OREGONSTATE/PRISM/AN81d')", "provider": "PRISM / OREGONSTATE", "state_date": "1981-01-01", - "end_date": "2024-11-08", + "end_date": "2024-11-09", "bbox": "-125, 24, -66, 50", "deprecated": false, "keywords": "climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather", @@ -13164,7 +13164,7 @@ "snippet": "ee.ImageCollection('TOMS/MERGED')", "provider": "NASA / GES DISC", "state_date": "1978-11-01", - "end_date": "2024-11-09", + "end_date": "2024-11-10", "bbox": "-180, -90, 180, 90", "deprecated": false, "keywords": "atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms", @@ -14820,7 +14820,7 @@ "snippet": "ee.ImageCollection('UTOKYO/WTLAB/KBDI/v1')", "provider": "Institute of Industrial Science, The University of Tokyo, Japan", "state_date": "2007-01-01", - "end_date": "2024-11-10", + "end_date": "2024-11-11", "bbox": "60, -60, 180, 60", "deprecated": false, "keywords": "drought, kbdi, lst_derived, rainfall, utokyo, wtlab", diff --git a/gee_catalog.tsv b/gee_catalog.tsv index 73f30f5..4be7ae8 100644 --- a/gee_catalog.tsv +++ b/gee_catalog.tsv @@ -5,7 +5,7 @@ ACA/reef_habitat/v2_0 Allen Coral Atlas (ACA) - Geomorphic Zonation and Benthic AHN/AHN2_05M_INT AHN Netherlands 0.5m DEM, Interpolated image ee.Image('AHN/AHN2_05M_INT') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_INT.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_INT CC0-1.0 AHN/AHN2_05M_NON AHN Netherlands 0.5m DEM, Non-Interpolated image ee.Image('AHN/AHN2_05M_NON') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_NON.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_NON CC0-1.0 AHN/AHN2_05M_RUW AHN Netherlands 0.5m DEM, Raw Samples image ee.Image('AHN/AHN2_05M_RUW') AHN 2012-01-01 2012-01-01 3.35, 50.74, 7.24, 53.55 False ahn, dem, elevation, geophysical, lidar, netherlands https://storage.googleapis.com/earthengine-stac/catalog/AHN/AHN_AHN2_05M_RUW.json https://developers.google.com/earth-engine/datasets/catalog/AHN_AHN2_05M_RUW CC0-1.0 -ASTER/AST_L1T_003 ASTER L1T Radiance image_collection ee.ImageCollection('ASTER/AST_L1T_003') NASA LP DAAC at the USGS EROS Center 2000-03-04 2024-11-10 -180, -90, 180, 90 False aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir https://storage.googleapis.com/earthengine-stac/catalog/ASTER/ASTER_AST_L1T_003.json https://developers.google.com/earth-engine/datasets/catalog/ASTER_AST_L1T_003 proprietary +ASTER/AST_L1T_003 ASTER L1T Radiance image_collection ee.ImageCollection('ASTER/AST_L1T_003') NASA LP DAAC at the USGS EROS Center 2000-03-04 2024-11-11 -180, -90, 180, 90 False aster, eos, imagery, nasa, nir, radiance, swir, terra, thermal, tir, toa, usgs, vnir https://storage.googleapis.com/earthengine-stac/catalog/ASTER/ASTER_AST_L1T_003.json https://developers.google.com/earth-engine/datasets/catalog/ASTER_AST_L1T_003 proprietary AU/GA/AUSTRALIA_5M_DEM Australian 5M DEM image_collection ee.ImageCollection('AU/GA/AUSTRALIA_5M_DEM') Geoscience Australia 2015-12-01 2015-12-01 114.09, -43.45, 153.64, -9.88 False australia, dem, elevation, ga, geophysical, geoscience_australia, lidar https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_AUSTRALIA_5M_DEM.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_AUSTRALIA_5M_DEM CC-BY-4.0 AU/GA/DEM_1SEC/v10/DEM-H DEM-H: Australian SRTM Hydrologically Enforced Digital Elevation Model image ee.Image('AU/GA/DEM_1SEC/v10/DEM-H') Geoscience Australia 2010-02-01 2010-02-01 112.99, -44.06, 154, -9.99 False australia, dem, elevation, ga, geophysical, geoscience_australia, smoothed, srtm https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_DEM_1SEC_v10_DEM-H.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_DEM_1SEC_v10_DEM-H CC-BY-4.0 AU/GA/DEM_1SEC/v10/DEM-S DEM-S: Australian Smoothed Digital Elevation Model image ee.Image('AU/GA/DEM_1SEC/v10/DEM-S') Geoscience Australia 2010-02-01 2010-02-01 112.99, -44.06, 154, -9.99 False australia, dem, elevation, ga, geophysical, geoscience_australia, smoothed, srtm https://storage.googleapis.com/earthengine-stac/catalog/AU/AU_GA_DEM_1SEC_v10_DEM-S.json https://developers.google.com/earth-engine/datasets/catalog/AU_GA_DEM_1SEC_v10_DEM-S CC-BY-4.0 @@ -39,31 +39,31 @@ COPERNICUS/CORINE/V20/100m Copernicus CORINE Land Cover image_collection ee.Imag COPERNICUS/DEM/GLO30 Copernicus DEM GLO-30: Global 30m Digital Elevation Model image_collection ee.ImageCollection('COPERNICUS/DEM/GLO30') Copernicus 2010-12-01 2015-01-31 -180, -90, 180, 90 False copernicus, dem, elevation, geophysical https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_DEM_GLO30.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_DEM_GLO30 proprietary COPERNICUS/Landcover/100m/Proba-V-C3/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 3 image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global') Copernicus 2015-01-01 2019-12-31 -180, -90, 180, 90 False copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V-C3_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global proprietary COPERNICUS/Landcover/100m/Proba-V/Global Copernicus Global Land Cover Layers: CGLS-LC100 Collection 2 [deprecated] image_collection ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V/Global') Copernicus 2015-01-01 2015-01-01 -180, -90, 180, 90 True copernicus, eea, esa, eu, landcover, proba, probav, vito https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_Landcover_100m_Proba-V_Global.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V_Global proprietary -COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2024-11-11 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary -COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-27 2024-11-11 -180, -56, 180, 83 True copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary -COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-27 2024-11-11 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary -COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-27 2024-11-11 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary -COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2024-11-11 -180, -56, 180, 83 True copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary -COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2024-11-11 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary -COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2024-11-10 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary -COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2024-11-11 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary -COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2024-11-11 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary -COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2024-11-11 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary -COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2024-11-11 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary -COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2024-11-11 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary -COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2024-11-11 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary -COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2024-11-11 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary -COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2024-11-11 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary +COPERNICUS/S1_GRD Sentinel-1 SAR GRD: C-band Synthetic Aperture Radar Ground Range Detected, log scaling image_collection ee.ImageCollection('COPERNICUS/S1_GRD') European Union/ESA/Copernicus 2014-10-03 2024-11-12 -180, -90, 180, 90 False backscatter, copernicus, esa, eu, polarization, radar, sar, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S1_GRD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S1_GRD proprietary +COPERNICUS/S2 Sentinel-2 MSI: MultiSpectral Instrument, Level-1C [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2') European Union/ESA/Copernicus 2015-06-27 2024-11-12 -180, -56, 180, 83 True copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2 proprietary +COPERNICUS/S2_CLOUD_PROBABILITY Sentinel-2: Cloud Probability image_collection ee.ImageCollection('COPERNICUS/S2_CLOUD_PROBABILITY') European Union/ESA/Copernicus/SentinelHub 2015-06-27 2024-11-12 -180, -56, 180, 83 False cloud, copernicus, esa, eu, msi, radiance, sentinel, sentinelhub https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_CLOUD_PROBABILITY.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_CLOUD_PROBABILITY proprietary +COPERNICUS/S2_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C image_collection ee.ImageCollection('COPERNICUS/S2_HARMONIZED') European Union/ESA/Copernicus 2015-06-27 2024-11-12 -180, -56, 180, 83 False copernicus, esa, eu, msi, radiance, sentinel https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_HARMONIZED proprietary +COPERNICUS/S2_SR Sentinel-2 MSI: MultiSpectral Instrument, Level-2A [deprecated] image_collection ee.ImageCollection('COPERNICUS/S2_SR') European Union/ESA/Copernicus 2017-03-28 2024-11-12 -180, -56, 180, 83 True copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR proprietary +COPERNICUS/S2_SR_HARMONIZED Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-2A image_collection ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') European Union/ESA/Copernicus 2017-03-28 2024-11-12 -180, -56, 180, 83 False copernicus, esa, eu, msi, reflectance, sentinel, sr https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S2_SR_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED proprietary +COPERNICUS/S3/OLCI Sentinel-3 OLCI EFR: Ocean and Land Color Instrument Earth Observation Full Resolution image_collection ee.ImageCollection('COPERNICUS/S3/OLCI') European Union/ESA/Copernicus 2016-10-18 2024-11-11 -180, -90, 180, 90 False copernicus, esa, eu, olci, radiance, sentinel, toa https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S3_OLCI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S3_OLCI proprietary +COPERNICUS/S5P/NRTI/L3_AER_AI Sentinel-5P NRTI AER AI: Near Real-Time UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_AI') European Union/ESA/Copernicus 2018-07-10 2024-11-12 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_AI proprietary +COPERNICUS/S5P/NRTI/L3_AER_LH Sentinel-5P NRTI AER LH: Near Real-Time UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_AER_LH') European Union/ESA/Copernicus 2018-07-10 2024-11-12 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_AER_LH proprietary +COPERNICUS/S5P/NRTI/L3_CLOUD Sentinel-5P NRTI CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CLOUD') European Union/ESA/Copernicus 2018-07-05 2024-11-12 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CLOUD proprietary +COPERNICUS/S5P/NRTI/L3_CO Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_CO') European Union/ESA/Copernicus 2018-11-22 2024-11-12 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_CO proprietary +COPERNICUS/S5P/NRTI/L3_HCHO Sentinel-5P NRTI HCHO: Near Real-Time Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_HCHO') European Union/ESA/Copernicus 2018-10-02 2024-11-12 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_HCHO proprietary +COPERNICUS/S5P/NRTI/L3_NO2 Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_NO2') European Union/ESA/Copernicus 2018-07-10 2024-11-12 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_NO2 proprietary +COPERNICUS/S5P/NRTI/L3_O3 Sentinel-5P NRTI O3: Near Real-Time Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_O3') European Union/ESA/Copernicus 2018-07-10 2024-11-12 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_O3 proprietary +COPERNICUS/S5P/NRTI/L3_SO2 Sentinel-5P NRTI SO2: Near Real-Time Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/NRTI/L3_SO2') European Union/ESA/Copernicus 2018-07-10 2024-11-12 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_NRTI_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_NRTI_L3_SO2 proprietary COPERNICUS/S5P/OFFL/L3_AER_AI Sentinel-5P OFFL AER AI: Offline UV Aerosol Index image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_AI') European Union/ESA/Copernicus 2018-07-04 2024-11-08 -180, -90, 180, 90 False aai, aerosol, air_quality, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_AI.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_AI proprietary COPERNICUS/S5P/OFFL/L3_AER_LH Sentinel-5P OFFL AER LH: Offline UV Aerosol Layer Height image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_AER_LH') European Union/ESA/Copernicus 2018-07-04 2024-11-03 -180, -90, 180, 90 False aerosol, air_quality, alh, copernicus, esa, eu, knmi, pollution, s5p, sentinel, tropomi, uvai https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_AER_LH.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_AER_LH proprietary COPERNICUS/S5P/OFFL/L3_CH4 Sentinel-5P OFFL CH4: Offline Methane image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4') European Union/ESA/Copernicus 2019-02-08 2024-11-08 -180, -90, 180, 90 False climate, copernicus, esa, eu, knmi, methane, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CH4.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4 proprietary COPERNICUS/S5P/OFFL/L3_CLOUD Sentinel-5P OFFL CLOUD: Near Real-Time Cloud image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD') European Union/ESA/Copernicus 2018-07-04 2024-11-08 -180, -90, 180, 90 False climate, cloud, copernicus, dlr, esa, eu, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CLOUD.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CLOUD proprietary COPERNICUS/S5P/OFFL/L3_CO Sentinel-5P OFFL CO: Offline Carbon Monoxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO') European Union/ESA/Copernicus 2018-06-28 2024-11-08 -180, -90, 180, 90 False air_quality, carbon_monoxide, copernicus, esa, eu, knmi, pollution, s5p, sentinel, sron, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_CO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CO proprietary -COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2024-11-07 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary -COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2024-11-02 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary -COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2024-11-07 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary -COPERNICUS/S5P/OFFL/L3_O3_TCL Sentinel-5P OFFL O3 TCL: Offline Tropospheric Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL') European Union/ESA/Copernicus 2018-04-30 2024-10-27 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3_TCL.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3_TCL proprietary -COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2024-11-07 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary +COPERNICUS/S5P/OFFL/L3_HCHO Sentinel-5P OFFL HCHO: Offline Formaldehyde image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO') European Union/ESA/Copernicus 2018-12-05 2024-11-08 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, formaldehyde, hcho, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_HCHO.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_HCHO proprietary +COPERNICUS/S5P/OFFL/L3_NO2 Sentinel-5P OFFL NO2: Offline Nitrogen Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2') European Union/ESA/Copernicus 2018-06-28 2024-11-03 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, knmi, nitrogen_dioxide, no2, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_NO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2 proprietary +COPERNICUS/S5P/OFFL/L3_O3 Sentinel-5P OFFL O3: Offline Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3') European Union/ESA/Copernicus 2018-09-08 2024-11-08 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3 proprietary +COPERNICUS/S5P/OFFL/L3_O3_TCL Sentinel-5P OFFL O3 TCL: Offline Tropospheric Ozone image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL') European Union/ESA/Copernicus 2018-04-30 2024-10-28 -180, -90, 180, 90 False air_quality, copernicus, esa, eu, o3, ozone, pollution, s5p, sentinel, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_O3_TCL.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_O3_TCL proprietary +COPERNICUS/S5P/OFFL/L3_SO2 Sentinel-5P OFFL SO2: Offline Sulfur Dioxide image_collection ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2') European Union/ESA/Copernicus 2018-12-05 2024-11-08 -180, -90, 180, 90 False air_quality, bira, copernicus, dlr, esa, eu, pollution, s5p, sentinel, so2, sulfur_dioxide, tropomi https://storage.googleapis.com/earthengine-stac/catalog/COPERNICUS/COPERNICUS_S5P_OFFL_L3_SO2.json https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_SO2 proprietary CPOM/CryoSat2/ANTARCTICA_DEM CryoSat-2 Antarctica 1km DEM image ee.Image('CPOM/CryoSat2/ANTARCTICA_DEM') CPOM 2010-07-01 2016-07-01 -180, -88, 180, -60 False antarctica, cpom, cryosat_2, dem, elevation, polar https://storage.googleapis.com/earthengine-stac/catalog/CPOM/CPOM_CryoSat2_ANTARCTICA_DEM.json https://developers.google.com/earth-engine/datasets/catalog/CPOM_CryoSat2_ANTARCTICA_DEM proprietary CSIC/SPEI/2_8 SPEIbase: Standardised Precipitation-Evapotranspiration Index database, Version 2.8 [deprecated] image_collection ee.ImageCollection('CSIC/SPEI/2_8') Spanish National Research Council (CSIC) 1901-01-01 2021-01-01 -180, -90, 180, 90 True climate, climate_change, drought, evapotranspiration, global, monthly, palmer, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/CSIC/CSIC_SPEI_2_8.json https://developers.google.com/earth-engine/datasets/catalog/CSIC_SPEI_2_8 CC-BY-4.0 CSIC/SPEI/2_9 SPEIbase: Standardised Precipitation-Evapotranspiration Index database, Version 2.9 image_collection ee.ImageCollection('CSIC/SPEI/2_9') Spanish National Research Council (CSIC) 1901-01-01 2023-01-01 -180, -90, 180, 90 False climate, climate_change, drought, evapotranspiration, global, monthly, palmer, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/CSIC/CSIC_SPEI_2_9.json https://developers.google.com/earth-engine/datasets/catalog/CSIC_SPEI_2_9 CC-BY-4.0 @@ -86,11 +86,11 @@ CSP/ERGo/1_0/US/topoDiversity US NED Topographic Diversity image ee.Image('CSP/E CSP/HM/GlobalHumanModification CSP gHM: Global Human Modification image_collection ee.ImageCollection('CSP/HM/GlobalHumanModification') Conservation Science Partners 2016-01-01 2016-12-31 -180, -90, 180, 90 False csp, fragmentation, human_modification, landcover, landscape_gradient, stressors, tnc https://storage.googleapis.com/earthengine-stac/catalog/CSP/CSP_HM_GlobalHumanModification.json https://developers.google.com/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification CC-BY-NC-SA-4.0 DLR/WSF/WSF2015/v1 World Settlement Footprint 2015 image ee.Image('DLR/WSF/WSF2015/v1') Deutsches Zentrum für Luft- und Raumfahrt (DLR) 2015-01-01 2016-01-01 -180, -90, 180, 90 False landcover, landsat_derived, sentinel1_derived, settlement, urban https://storage.googleapis.com/earthengine-stac/catalog/DLR/DLR_WSF_WSF2015_v1.json https://developers.google.com/earth-engine/datasets/catalog/DLR_WSF_WSF2015_v1 CC0-1.0 DOE/ORNL/LandScan_HD/Ukraine_202201 LandScan High Definition Data for Ukraine, January 2022 image ee.Image('DOE/ORNL/LandScan_HD/Ukraine_202201') Oak Ridge National Laboratory 2022-01-01 2022-02-01 22.125, 44.175, 40.225, 52.4 False landscan, population, ukraine https://storage.googleapis.com/earthengine-stac/catalog/DOE/DOE_ORNL_LandScan_HD_Ukraine_202201.json https://developers.google.com/earth-engine/datasets/catalog/DOE_ORNL_LandScan_HD_Ukraine_202201 CC-BY-4.0 -ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2024-11-11 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary +ECMWF/CAMS/NRT Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time image_collection ee.ImageCollection('ECMWF/CAMS/NRT') European Centre for Medium-Range Weather Forecasts (ECMWF) 2016-06-22 2024-11-12 -180, -90, 180, 90 False aerosol, atmosphere, climate, copernicus, ecmwf, forecast, particulate_matter https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_CAMS_NRT.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_CAMS_NRT proprietary ECMWF/ERA5/DAILY ERA5 Daily Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/DAILY') ECMWF / Copernicus Climate Change Service 1979-01-02 2020-07-09 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_DAILY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_DAILY proprietary ECMWF/ERA5/MONTHLY ERA5 Monthly Aggregates - Latest Climate Reanalysis Produced by ECMWF / Copernicus Climate Change Service image_collection ee.ImageCollection('ECMWF/ERA5/MONTHLY') ECMWF / Copernicus Climate Change Service 1979-01-01 2020-06-01 -180, -90, 180, 90 False climate, copernicus, dewpoint, ecmwf, era5, precipitation, pressure, reanalysis, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_MONTHLY proprietary -ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2024-11-03 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary -ECMWF/ERA5_LAND/HOURLY ERA5-Land Hourly - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY') Copernicus Climate Data Store 1950-01-01 2024-11-05 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_HOURLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_HOURLY proprietary +ECMWF/ERA5_LAND/DAILY_AGGR ERA5-Land Daily Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/DAILY_AGGR') Daily Aggregates: Google and Copernicus Climate Data Store 1950-01-02 2024-11-05 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_DAILY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_AGGR proprietary +ECMWF/ERA5_LAND/HOURLY ERA5-Land Hourly - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY') Copernicus Climate Data Store 1950-01-01 2024-11-06 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_HOURLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_HOURLY proprietary ECMWF/ERA5_LAND/MONTHLY ERA5-Land Monthly Averaged - ECMWF Climate Reanalysis [deprecated] image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY') Copernicus Climate Data Store 1950-02-01 2023-04-01 -180, -90, 180, 90 True cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY proprietary ECMWF/ERA5_LAND/MONTHLY_AGGR ERA5-Land Monthly Aggregated - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR') Monthly Aggregates: Google and Copernicus Climate Data Store 1950-02-01 2024-10-01 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY_AGGR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY_AGGR proprietary ECMWF/ERA5_LAND/MONTHLY_BY_HOUR ERA5-Land Monthly Averaged by Hour of Day - ECMWF Climate Reanalysis image_collection ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_BY_HOUR') Climate Data Store 1950-01-01 2024-10-01 -180, -90, 180, 90 False cds, climate, copernicus, ecmwf, era5_land, evaporation, heat, lakes, precipitation, pressure, radiation, reanalysis, runoff, snow, soil_water, temperature, vegetation, wind https://storage.googleapis.com/earthengine-stac/catalog/ECMWF/ECMWF_ERA5_LAND_MONTHLY_BY_HOUR.json https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_MONTHLY_BY_HOUR proprietary @@ -132,7 +132,7 @@ FAO/WAPOR/2/L1_NPP_D WAPOR Dekadal Net Primary Production 2.0 image_collection e FAO/WAPOR/2/L1_RET_D WAPOR Dekadal Reference Evapotranspiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_RET_D') FAO UN 2009-01-01 2023-03-11 -30.15, -39.9953437, 65.13, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_RET_D.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_RET_D proprietary FAO/WAPOR/2/L1_RET_E WAPOR Daily Reference Evapotranspiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_RET_E') FAO UN 2009-01-01 2023-03-20 -30.15, -39.9953437, 65.13, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_RET_E.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_RET_E proprietary FAO/WAPOR/2/L1_T_D WAPOR Dekadal Transpiration 2.0 image_collection ee.ImageCollection('FAO/WAPOR/2/L1_T_D') FAO UN 2009-01-01 2023-03-01 -30.0044643, -40.0044644, 65.0044644, 40.0044643 False agriculture, fao, wapor, water https://storage.googleapis.com/earthengine-stac/catalog/FAO/FAO_WAPOR_2_L1_T_D.json https://developers.google.com/earth-engine/datasets/catalog/FAO_WAPOR_2_L1_T_D proprietary -FIRMS FIRMS: Fire Information for Resource Management System image_collection ee.ImageCollection('FIRMS') NASA / LANCE / EOSDIS 2000-11-01 2024-11-10 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal https://storage.googleapis.com/earthengine-stac/catalog/FIRMS/FIRMS.json https://developers.google.com/earth-engine/datasets/catalog/FIRMS proprietary +FIRMS FIRMS: Fire Information for Resource Management System image_collection ee.ImageCollection('FIRMS') NASA / LANCE / EOSDIS 2000-11-01 2024-11-11 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal https://storage.googleapis.com/earthengine-stac/catalog/FIRMS/FIRMS.json https://developers.google.com/earth-engine/datasets/catalog/FIRMS proprietary FORMA/FORMA_500m FORMA Global Forest Watch Deforestation Alerts, 500m [deprecated] image ee.Image('FORMA/FORMA_500m') Global Forest Watch, World Resources Institute 2006-01-01 2015-06-10 -180, -90, 180, 90 True alerts, deforestation, forest, forma, geophysical, gfw, modis, nasa, wri https://storage.googleapis.com/earthengine-stac/catalog/FORMA/FORMA_FORMA_500m.json https://developers.google.com/earth-engine/datasets/catalog/FORMA_FORMA_500m proprietary Finland/MAVI/VV/50cm Finland NRG NLS orthophotos 50 cm by Mavi image_collection ee.ImageCollection('Finland/MAVI/VV/50cm') NLS orthophotos 2015-01-01 2018-01-01 18, 59, 29.2, 69.4 False falsecolor, finland, mavi, nrg, orthophoto https://storage.googleapis.com/earthengine-stac/catalog/Finland/Finland_MAVI_VV_50cm.json https://developers.google.com/earth-engine/datasets/catalog/Finland_MAVI_VV_50cm CC-BY-4.0 Finland/SMK/V/50cm Finland RGB NLS orthophotos 50 cm by SMK image_collection ee.ImageCollection('Finland/SMK/V/50cm') NLS orthophotos 2015-01-01 2023-01-01 18, 59, 29.2, 69.4 False finland, orthophoto, rgb, smk https://storage.googleapis.com/earthengine-stac/catalog/Finland/Finland_SMK_V_50cm.json https://developers.google.com/earth-engine/datasets/catalog/Finland_SMK_V_50cm proprietary @@ -148,8 +148,8 @@ GLIMS/20230607 GLIMS 2023: Global Land Ice Measurements From Space table ee.Feat GLIMS/current GLIMS Current: Global Land Ice Measurements From Space table ee.FeatureCollection('GLIMS/current') National Snow and Ice Data Center (NSDIC) 1750-01-01 2023-06-07 -180, -90, 180, 90 False glacier, glims, ice, landcover, nasa, nsidc, snow https://storage.googleapis.com/earthengine-stac/catalog/GLIMS/GLIMS_current.json https://developers.google.com/earth-engine/datasets/catalog/GLIMS_current proprietary GLOBAL_FLOOD_DB/MODIS_EVENTS/V1 Global Flood Database v1 (2000-2018) image_collection ee.ImageCollection('GLOBAL_FLOOD_DB/MODIS_EVENTS/V1') Cloud to Street (C2S) / Dartmouth Flood Observatory (DFO) 2000-02-17 2018-12-10 -180, -90, 180, 90 False c2s, cloudtostreet, dartmouth, dfo, flood, gfd, inundation, surface, water https://storage.googleapis.com/earthengine-stac/catalog/GLOBAL_FLOOD_DB/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1.json https://developers.google.com/earth-engine/datasets/catalog/GLOBAL_FLOOD_DB_MODIS_EVENTS_V1 CC-BY-NC-4.0 GOOGLE/AirView/California_Unified_2015_2019 Google Street View Air Quality: High Resolution Air Pollution Mapping in California table ee.FeatureCollection('GOOGLE/AirView/California_Unified_2015_2019') Google / Aclima 2015-05-28 2019-06-07 -180, -90, 180, 90 False air_quality, nitrogen_dioxide, pollution https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_AirView_California_Unified_2015_2019.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_AirView_California_Unified_2015_2019 CC-BY-NC-4.0 -GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2015-06-27 2024-11-11 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 -GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-27 2024-11-11 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 +GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED Cloud Score+ S2_HARMONIZED V1 image_collection ee.ImageCollection('GOOGLE/CLOUD_SCORE_PLUS/V1/S2_HARMONIZED') Google Earth Engine 2015-06-27 2024-11-12 -180, -90, 180, 90 False google, cloud, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_CLOUD_SCORE_PLUS_V1_S2_HARMONIZED CC-BY-4.0 +GOOGLE/DYNAMICWORLD/V1 Dynamic World V1 image_collection ee.ImageCollection('GOOGLE/DYNAMICWORLD/V1') World Resources Institute 2015-06-27 2024-11-12 -180, -90, 180, 90 False global, google, landcover, landuse, nrt, sentinel2_derived https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_DYNAMICWORLD_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1 CC-BY-4.0 GOOGLE/GLOBAL_CCDC/V1 Google Global Landsat-based CCDC Segments (1999-2019) image_collection ee.ImageCollection('GOOGLE/GLOBAL_CCDC/V1') Google 1999-01-01 2020-01-01 -180, -60, 180, 72 False change_detection, google, landcover, landsat_derived, landuse https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_GLOBAL_CCDC_V1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_GLOBAL_CCDC_V1 CC-BY-4.0 GOOGLE/Research/open-buildings-temporal/v1 Open Buildings Temporal V1 image_collection ee.ImageCollection('GOOGLE/Research/open-buildings-temporal/v1') Google Research - Open Buildings 2016-06-30 2023-06-30 -180, -90, 180, 90 False building_height, height, annual, built_up, open_buildings, africa, asia, south_asia, southeast_asia, high_resolution https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings-temporal_v1.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings-temporal_v1 CC-BY-4.0 GOOGLE/Research/open-buildings/v1/polygons Open Buildings V1 Polygons [deprecated] table ee.FeatureCollection('GOOGLE/Research/open-buildings/v1/polygons') Google Research - Open Buildings 2021-04-30 2021-04-30 -180, -90, 180, 90 True africa, building, built_up, open_buildings, structure https://storage.googleapis.com/earthengine-stac/catalog/GOOGLE/GOOGLE_Research_open-buildings_v1_polygons.json https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v1_polygons CC-BY-4.0 @@ -165,7 +165,7 @@ HYCOM/GLBu0_08/sea_water_velocity HYCOM: Hybrid Coordinate Ocean Model, Water Ve HYCOM/sea_surface_elevation HYCOM: Hybrid Coordinate Ocean Model, Sea Surface Elevation image_collection ee.ImageCollection('HYCOM/sea_surface_elevation') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False elevation, hycom, nopp, ocean, ssh, water https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_surface_elevation.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_surface_elevation proprietary HYCOM/sea_temp_salinity HYCOM: Hybrid Coordinate Ocean Model, Water Temperature and Salinity image_collection ee.ImageCollection('HYCOM/sea_temp_salinity') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False hycom, nopp, ocean, salinity, sst, water, water_temp https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_temp_salinity.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_temp_salinity proprietary HYCOM/sea_water_velocity HYCOM: Hybrid Coordinate Ocean Model, Water Velocity image_collection ee.ImageCollection('HYCOM/sea_water_velocity') NOPP 1992-10-02 2024-09-05 -180, -80.48, 180, 80.48 False hycom, nopp, ocean, velocity, water https://storage.googleapis.com/earthengine-stac/catalog/HYCOM/HYCOM_sea_water_velocity.json https://developers.google.com/earth-engine/datasets/catalog/HYCOM_sea_water_velocity proprietary -IDAHO_EPSCOR/GRIDMET GRIDMET: University of Idaho Gridded Surface Meteorological Dataset image_collection ee.ImageCollection('IDAHO_EPSCOR/GRIDMET') University of California Merced 1979-01-01 2024-11-09 -124.9, 24.9, -66.8, 49.6 False climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_GRIDMET.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_GRIDMET proprietary +IDAHO_EPSCOR/GRIDMET GRIDMET: University of Idaho Gridded Surface Meteorological Dataset image_collection ee.ImageCollection('IDAHO_EPSCOR/GRIDMET') University of California Merced 1979-01-01 2024-11-10 -124.9, 24.9, -66.8, 49.6 False climate, fireburning, gridmet, humidity, merced, metdata, nfdrs, precipitation, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_GRIDMET.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_GRIDMET proprietary IDAHO_EPSCOR/MACAv2_METDATA MACAv2-METDATA: University of Idaho, Multivariate Adaptive Constructed Analogs Applied to Global Climate Models image_collection ee.ImageCollection('IDAHO_EPSCOR/MACAv2_METDATA') University of California Merced 1900-01-01 2100-12-31 -124.9, 24.9, -67, 49.6 False climate, conus, geophysical, idaho, maca, monthly https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_MACAv2_METDATA.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_MACAv2_METDATA CC0-1.0 IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY MACAv2-METDATA Monthly Summaries: University of Idaho, Multivariate Adaptive Constructed Analogs Applied to Global Climate Models image_collection ee.ImageCollection('IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY') University of California Merced 1900-01-01 2099-12-31 -124.9, 24.9, -67, 49.6 False climate, conus, geophysical, idaho, maca, monthly https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_MACAv2_METDATA_MONTHLY.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_MACAv2_METDATA_MONTHLY CC0-1.0 IDAHO_EPSCOR/PDSI PDSI: University of Idaho Palmer Drought Severity Index [deprecated] image_collection ee.ImageCollection('IDAHO_EPSCOR/PDSI') University of California Merced 1979-03-01 2020-06-20 -124.9, 24.9, -66.8, 49.6 True climate, conus, crop, drought, geophysical, merced, palmer, pdsi https://storage.googleapis.com/earthengine-stac/catalog/IDAHO_EPSCOR/IDAHO_EPSCOR_PDSI.json https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_PDSI proprietary @@ -207,20 +207,20 @@ JAXA/ALOS/PALSAR/YEARLY/SAR Global PALSAR-2/PALSAR Yearly Mosaic, version 1 imag JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH Global PALSAR-2/PALSAR Yearly Mosaic, version 2 image_collection ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/SAR_EPOCH') JAXA EORC 2015-01-01 2023-01-01 -180, -90, 180, 90 False alos, alos2, eroc, jaxa, palsar, palsar2, sar https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_ALOS_PALSAR_YEARLY_SAR_EPOCH.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR_EPOCH proprietary JAXA/GCOM-C/L3/LAND/LAI/V1 GCOM-C/SGLI L3 Leaf Area Index (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V1 proprietary JAXA/GCOM-C/L3/LAND/LAI/V2 GCOM-C/SGLI L3 Leaf Area Index (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V2 proprietary -JAXA/GCOM-C/L3/LAND/LAI/V3 GCOM-C/SGLI L3 Leaf Area Index (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-09 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V3 proprietary +JAXA/GCOM-C/L3/LAND/LAI/V3 GCOM-C/SGLI L3 Leaf Area Index (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LAI/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-10 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, lai, land, leaf_area_index https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LAI_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LAI_V3 proprietary JAXA/GCOM-C/L3/LAND/LST/V1 GCOM-C/SGLI L3 Land Surface Temperature (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V1 proprietary JAXA/GCOM-C/L3/LAND/LST/V2 GCOM-C/SGLI L3 Land Surface Temperature (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V2 proprietary -JAXA/GCOM-C/L3/LAND/LST/V3 GCOM-C/SGLI L3 Land Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-09 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V3 proprietary +JAXA/GCOM-C/L3/LAND/LST/V3 GCOM-C/SGLI L3 Land Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/LAND/LST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-10 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, land, land_surface_temperature, lst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_LAND_LST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_LAND_LST_V3 proprietary JAXA/GCOM-C/L3/OCEAN/CHLA/V1 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V1 proprietary JAXA/GCOM-C/L3/OCEAN/CHLA/V2 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V2 proprietary -JAXA/GCOM-C/L3/OCEAN/CHLA/V3 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-09 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V3 proprietary +JAXA/GCOM-C/L3/OCEAN/CHLA/V3 GCOM-C/SGLI L3 Chlorophyll-a Concentration (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/CHLA/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-10 -180, -90, 180, 90 False chla, chlorophyll_a, climate, g_portal, gcom, gcom_c, jaxa, ocean, ocean_color https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_CHLA_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_CHLA_V3 proprietary JAXA/GCOM-C/L3/OCEAN/SST/V1 GCOM-C/SGLI L3 Sea Surface Temperature (V1) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V1') Global Change Observation Mission (GCOM) 2018-01-01 2020-06-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V1.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V1 proprietary JAXA/GCOM-C/L3/OCEAN/SST/V2 GCOM-C/SGLI L3 Sea Surface Temperature (V2) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V2') Global Change Observation Mission (GCOM) 2018-01-01 2021-11-28 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V2.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V2 proprietary -JAXA/GCOM-C/L3/OCEAN/SST/V3 GCOM-C/SGLI L3 Sea Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-09 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V3 proprietary -JAXA/GPM_L3/GSMaP/v6/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V6 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-11 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_operational proprietary +JAXA/GCOM-C/L3/OCEAN/SST/V3 GCOM-C/SGLI L3 Sea Surface Temperature (V3) image_collection ee.ImageCollection('JAXA/GCOM-C/L3/OCEAN/SST/V3') Global Change Observation Mission (GCOM) 2021-11-29 2024-11-10 -180, -90, 180, 90 False climate, g_portal, gcom, gcom_c, jaxa, ocean, sea_surface_temperature, sst https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GCOM-C_L3_OCEAN_SST_V3.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GCOM-C_L3_OCEAN_SST_V3 proprietary +JAXA/GPM_L3/GSMaP/v6/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V6 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-12 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_operational proprietary JAXA/GPM_L3/GSMaP/v6/reanalysis GSMaP Reanalysis: Global Satellite Mapping of Precipitation image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v6/reanalysis') JAXA Earth Observation Research Center 2000-03-01 2014-03-12 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v6_reanalysis.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v6_reanalysis proprietary -JAXA/GPM_L3/GSMaP/v7/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V7 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-11 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v7_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v7_operational proprietary -JAXA/GPM_L3/GSMaP/v8/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V8 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational') JAXA Earth Observation Research Center 1998-01-01 2024-11-11 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v8_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v8_operational proprietary +JAXA/GPM_L3/GSMaP/v7/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V7 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v7/operational') JAXA Earth Observation Research Center 2014-03-01 2024-11-12 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v7_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v7_operational proprietary +JAXA/GPM_L3/GSMaP/v8/operational GSMaP Operational: Global Satellite Mapping of Precipitation - V8 image_collection ee.ImageCollection('JAXA/GPM_L3/GSMaP/v8/operational') JAXA Earth Observation Research Center 1998-01-01 2024-11-12 -180, -60, 180, 60 False climate, geophysical, gpm, hourly, jaxa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/JAXA/JAXA_GPM_L3_GSMaP_v8_operational.json https://developers.google.com/earth-engine/datasets/catalog/JAXA_GPM_L3_GSMaP_v8_operational proprietary JCU/Murray/GIC/global_tidal_wetland_change/2019 Murray Global Tidal Wetland Change v1.0 (1999-2019) image ee.Image('JCU/Murray/GIC/global_tidal_wetland_change/2019') Murray/JCU 1999-01-01 2019-12-31 -180, -90, 180, 90 False coastal, ecosystem, intertidal, landsat_derived, mangrove, murray, saltmarsh, tidal_flat, tidal_marsh https://storage.googleapis.com/earthengine-stac/catalog/JCU/JCU_Murray_GIC_global_tidal_wetland_change_2019.json https://developers.google.com/earth-engine/datasets/catalog/JCU_Murray_GIC_global_tidal_wetland_change_2019 CC-BY-4.0 JRC/CEMS_GLOFAS/FloodHazard/v1 JRC Global River Flood Hazard Maps Version 1 image_collection ee.ImageCollection('JRC/CEMS_GLOFAS/FloodHazard/v1') Joint Research Centre 2024-03-16 2024-03-16 -180, -90, 180, 90 False flood, monitoring, wri https://storage.googleapis.com/earthengine-stac/catalog/JRC/JRC_CEMS_GLOFAS_FloodHazard_v1.json https://developers.google.com/earth-engine/datasets/catalog/JRC_CEMS_GLOFAS_FloodHazard_v1 CC-BY-4.0 JRC/D5/EUCROPMAP/V1 EUCROPMAP image_collection ee.ImageCollection('JRC/D5/EUCROPMAP/V1') Joint Research Center (JRC) 2018-01-01 2022-01-01 -16.171875, 34.313433, 36.386719, 72.182526 False crop, eu, jrc, lucas, sentinel1_derived https://storage.googleapis.com/earthengine-stac/catalog/JRC/JRC_D5_EUCROPMAP_V1.json https://developers.google.com/earth-engine/datasets/catalog/JRC_D5_EUCROPMAP_V1 CC-BY-4.0 @@ -304,16 +304,16 @@ LANDSAT/GLS2005_L5 Landsat Global Land Survey 2005, Landsat 5 scenes image_colle LANDSAT/GLS2005_L7 Landsat Global Land Survey 2005, Landsat 7 scenes image_collection ee.ImageCollection('LANDSAT/GLS2005_L7') USGS 2003-07-29 2008-07-29 -180, -90, 180, 90 False etm, gls, l7, landsat, radiance, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_GLS2005_L7.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_GLS2005_L7 PDDL-1.0 LANDSAT/LC08/C02/T1 USGS Landsat 8 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1') USGS 2013-03-18 2024-11-09 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1 PDDL-1.0 LANDSAT/LC08/C02/T1_L2 USGS Landsat 8 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_L2') USGS 2013-03-18 2024-11-02 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l8sr, landsat, lasrc, lc08, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2 proprietary -LANDSAT/LC08/C02/T1_RT USGS Landsat 8 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT') USGS 2013-03-18 2024-11-11 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT PDDL-1.0 -LANDSAT/LC08/C02/T1_RT_TOA USGS Landsat 8 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA') USGS/Google 2013-03-18 2024-11-11 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT_TOA PDDL-1.0 +LANDSAT/LC08/C02/T1_RT USGS Landsat 8 Collection 2 Tier 1 and Real-Time data Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT') USGS 2013-03-18 2024-11-12 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, nrt, oli_tirs, radiance, rt, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT PDDL-1.0 +LANDSAT/LC08/C02/T1_RT_TOA USGS Landsat 8 Collection 2 Tier 1 and Real-Time data TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_RT_TOA') USGS/Google 2013-03-18 2024-11-12 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_RT_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_RT_TOA PDDL-1.0 LANDSAT/LC08/C02/T1_TOA USGS Landsat 8 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA') USGS/Google 2013-03-18 2024-11-09 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_TOA PDDL-1.0 LANDSAT/LC08/C02/T2 USGS Landsat 8 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2') USGS 2021-10-28 2024-11-09 -180, -90, 180, 90 False c2, global, l8, landsat, lc8, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2 PDDL-1.0 LANDSAT/LC08/C02/T2_L2 USGS Landsat 8 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_L2') USGS 2013-03-18 2024-11-02 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l8sr, landsat, lasrc, lc08, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_L2 proprietary LANDSAT/LC08/C02/T2_TOA USGS Landsat 8 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC08/C02/T2_TOA') USGS/Google 2021-10-28 2024-11-09 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC08_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T2_TOA PDDL-1.0 -LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2024-11-11 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 +LANDSAT/LC09/C02/T1 USGS Landsat 9 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1') USGS 2021-10-31 2024-11-12 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1 PDDL-1.0 LANDSAT/LC09/C02/T1_L2 USGS Landsat 9 Level 2, Collection 2, Tier 1 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') USGS 2021-10-31 2024-11-09 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_L2 proprietary -LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2024-11-11 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 -LANDSAT/LC09/C02/T2 USGS Landsat 9 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2') USGS 2021-11-02 2024-11-11 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2 PDDL-1.0 +LANDSAT/LC09/C02/T1_TOA USGS Landsat 9 Collection 2 Tier 1 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T1_TOA') USGS/Google 2021-10-31 2024-11-12 -180, -90, 180, 90 False c2, global, landsat, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T1_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T1_TOA PDDL-1.0 +LANDSAT/LC09/C02/T2 USGS Landsat 9 Collection 2 Tier 2 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2') USGS 2021-11-02 2024-11-12 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, oli_tirs, radiance, t2, tier2, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2 PDDL-1.0 LANDSAT/LC09/C02/T2_L2 USGS Landsat 9 Level 2, Collection 2, Tier 2 image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_L2') USGS 2021-10-31 2024-11-09 -180, -90, 180, 90 False cfmask, cloud, fmask, global, l9sr, landsat, lasrc, lc09, lst, reflectance, sr, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_L2.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_L2 proprietary LANDSAT/LC09/C02/T2_TOA USGS Landsat 9 Collection 2 Tier 2 TOA Reflectance image_collection ee.ImageCollection('LANDSAT/LC09/C02/T2_TOA') USGS/Google 2021-11-02 2024-11-11 -180, -90, 180, 90 False c2, global, l9, landsat, lc9, toa, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LC09_C02_T2_TOA.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC09_C02_T2_TOA PDDL-1.0 LANDSAT/LE07/C02/T1 USGS Landsat 7 Collection 2 Tier 1 Raw Scenes image_collection ee.ImageCollection('LANDSAT/LE07/C02/T1') USGS 1999-05-28 2024-01-19 -180, -90, 180, 90 False c2, etm, global, l7, landsat, le7, radiance, t1, tier1, usgs https://storage.googleapis.com/earthengine-stac/catalog/LANDSAT/LANDSAT_LE07_C02_T1.json https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1 PDDL-1.0 @@ -537,16 +537,16 @@ MODIS/MYD13A1 MYD13A1.005 Vegetation Indices 16-Day L3 Global 500m [deprecated] MODIS/MYD13Q1 MYD13Q1.005 Vegetation Indices 16-Day Global 250m [deprecated] image_collection ee.ImageCollection('MODIS/MYD13Q1') NASA LP DAAC at the USGS EROS Center 2002-07-04 2017-03-14 -180, -90, 180, 90 True 16_day, aqua, evi, global, modis, myd13q1, ndvi, vegetation https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_MYD13Q1.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_MYD13Q1 proprietary MODIS/NTSG/MOD16A2/105 MOD16A2: MODIS Global Terrestrial Evapotranspiration 8-Day Global 1km image_collection ee.ImageCollection('MODIS/NTSG/MOD16A2/105') Numerical Terradynamic Simulation Group, The University of Montana 2000-01-01 2014-12-27 -180, -90, 180, 90 False 8_day, evapotranspiration, global, mod16a2, modis https://storage.googleapis.com/earthengine-stac/catalog/MODIS/MODIS_NTSG_MOD16A2_105.json https://developers.google.com/earth-engine/datasets/catalog/MODIS_NTSG_MOD16A2_105 proprietary NASA/ASTER_GED/AG100_003 AG100: ASTER Global Emissivity Dataset 100-meter V003 image ee.Image('NASA/ASTER_GED/AG100_003') NASA LP DAAC at the USGS EROS Center 2000-01-01 2008-12-31 -180, -59, 180, 80 False aster, caltech, elevation, emissivity, ged, geophysical, infrared, jpl, lst, nasa, ndvi, temperature, thermal https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_ASTER_GED_AG100_003.json https://developers.google.com/earth-engine/datasets/catalog/NASA_ASTER_GED_AG100_003 proprietary -NASA/EMIT/L1B/RAD EMIT L1B At-Sensor Calibrated Radiance and Geolocation Data 60 m image_collection ee.ImageCollection('NASA/EMIT/L1B/RAD') NASA Jet Propulsion Laboratory 2022-08-09 2024-11-10 -180, -90, 180, 90 False daily, emit, nasa, radiance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L1B_RAD.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L1B_RAD proprietary -NASA/EMIT/L2A/RFL EMIT L2A Estimated Surface Reflectance and Uncertainty and Masks 60 m image_collection ee.ImageCollection('NASA/EMIT/L2A/RFL') NASA Jet Propulsion Laboratory 2022-08-09 2024-11-10 -180, -90, 180, 90 False daily, emit, nasa, reflectance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2A_RFL.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2A_RFL proprietary +NASA/EMIT/L1B/RAD EMIT L1B At-Sensor Calibrated Radiance and Geolocation Data 60 m image_collection ee.ImageCollection('NASA/EMIT/L1B/RAD') NASA Jet Propulsion Laboratory 2022-08-09 2024-11-11 -180, -90, 180, 90 False daily, emit, nasa, radiance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L1B_RAD.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L1B_RAD proprietary +NASA/EMIT/L2A/RFL EMIT L2A Estimated Surface Reflectance and Uncertainty and Masks 60 m image_collection ee.ImageCollection('NASA/EMIT/L2A/RFL') NASA Jet Propulsion Laboratory 2022-08-09 2024-11-11 -180, -90, 180, 90 False daily, emit, nasa, reflectance https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2A_RFL.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2A_RFL proprietary NASA/EMIT/L2B/CH4ENH Earth Surface Mineral Dust Source Investigation- Methane Enhancement image_collection ee.ImageCollection('NASA/EMIT/L2B/CH4ENH') NASA Jet Propulsion Laboratory 2022-08-10 2024-10-05 -180, -90, 180, 90 False daily, emit, nasa, methane https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2B_CH4ENH.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2B_CH4ENH proprietary NASA/EMIT/L2B/CH4PLM Earth Surface Mineral Dust Source Investigation- Methane Plume Complexes image_collection ee.ImageCollection('NASA/EMIT/L2B/CH4PLM') NASA Jet Propulsion Laboratory 2022-08-10 2024-09-30 -180, -90, 180, 90 False daily, emit, nasa, methane https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_EMIT_L2B_CH4PLM.json https://developers.google.com/earth-engine/datasets/catalog/NASA_EMIT_L2B_CH4PLM proprietary NASA/FLDAS/NOAH01/C/GL/M/V001 FLDAS: Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System image_collection ee.ImageCollection('NASA/FLDAS/NOAH01/C/GL/M/V001') NASA GES DISC at NASA Goddard Space Flight Center 1982-01-01 2024-09-01 -180, -60, 180, 90 False climate, evapotranspiration, famine, fldas, humidity, ldas, monthly, nasa, runoff, snow, soil_moisture, soil_temperature, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_FLDAS_NOAH01_C_GL_M_V001.json https://developers.google.com/earth-engine/datasets/catalog/NASA_FLDAS_NOAH01_C_GL_M_V001 proprietary NASA/GDDP-CMIP6 NEX-GDDP-CMIP6: NASA Earth Exchange Global Daily Downscaled Climate Projections image_collection ee.ImageCollection('NASA/GDDP-CMIP6') NASA / Climate Analytics Group 1950-01-01 2100-12-31 -180, -90, 180, 90 False cag, climate, gddp, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GDDP-CMIP6.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GDDP-CMIP6 various -NASA/GEOS-CF/v1/fcst/htf GEOS-CF fcst htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf') NASA / GMAO 2022-10-01 2024-11-10 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_htf proprietary -NASA/GEOS-CF/v1/fcst/tavg1hr GEOS-CF fcst tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr') NASA / GMAO 2022-10-01 2024-11-10 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_tavg1hr proprietary -NASA/GEOS-CF/v1/rpl/htf GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf') NASA / GMAO 2018-01-01 2024-11-10 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf proprietary -NASA/GEOS-CF/v1/rpl/tavg1hr GEOS-CF rpl tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr') NASA / GMAO 2018-01-01 2024-11-10 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_tavg1hr proprietary +NASA/GEOS-CF/v1/fcst/htf GEOS-CF fcst htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/htf') NASA / GMAO 2022-10-01 2024-11-11 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_htf proprietary +NASA/GEOS-CF/v1/fcst/tavg1hr GEOS-CF fcst tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/fcst/tavg1hr') NASA / GMAO 2022-10-01 2024-11-11 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_fcst_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_tavg1hr proprietary +NASA/GEOS-CF/v1/rpl/htf GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf') NASA / GMAO 2018-01-01 2024-11-11 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_htf.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf proprietary +NASA/GEOS-CF/v1/rpl/tavg1hr GEOS-CF rpl tavg1hr v1: Goddard Earth Observing System Composition Forecast image_collection ee.ImageCollection('NASA/GEOS-CF/v1/rpl/tavg1hr') NASA / GMAO 2018-01-01 2024-11-11 -180, -90, 180, 90 False composition, forecast, geos, gmao, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GEOS-CF_v1_rpl_tavg1hr.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_tavg1hr proprietary NASA/GIMMS/3GV0 GIMMS NDVI From AVHRR Sensors (3rd Generation) image_collection ee.ImageCollection('NASA/GIMMS/3GV0') NASA/NOAA 1981-07-01 2013-12-16 -180, -90, 180, 90 False avhrr, gimms, nasa, ndvi, noaa, vegetation https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GIMMS_3GV0.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GIMMS_3GV0 proprietary NASA/GLDAS/V021/NOAH/G025/T3H GLDAS-2.1: Global Land Data Assimilation System image_collection ee.ImageCollection('NASA/GLDAS/V021/NOAH/G025/T3H') NASA GES DISC at NASA Goddard Space Flight Center 2000-01-01 2024-10-20 -180, -90, 180, 90 False 3_hourly, climate, evaporation, forcing, geophysical, gldas, humidity, ldas, nasa, precipitation, pressure, radiation, soil, soil_moisture, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GLDAS_V021_NOAH_G025_T3H.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V021_NOAH_G025_T3H proprietary NASA/GLDAS/V022/CLSM/G025/DA1D GLDAS-2.2: Global Land Data Assimilation System image_collection ee.ImageCollection('NASA/GLDAS/V022/CLSM/G025/DA1D') NASA GES DISC at NASA Goddard Earth Sciences Data and Information Services Center 2003-01-01 2024-05-31 -180, -90, 180, 90 False 3_hourly, climate, evaporation, forcing, geophysical, gldas, humidity, ldas, nasa, precipitation, pressure, radiation, soil, soil_moisture, surface, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GLDAS_V022_CLSM_G025_DA1D.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V022_CLSM_G025_DA1D proprietary @@ -554,7 +554,7 @@ NASA/GLDAS/V20/NOAH/G025/T3H Reprocessed GLDAS-2.0: Global Land Data Assimilatio NASA/GPM_L3/IMERG_MONTHLY_V06 GPM: Monthly Global Precipitation Measurement (GPM) v6 image_collection ee.ImageCollection('NASA/GPM_L3/IMERG_MONTHLY_V06') NASA GES DISC at NASA Goddard Space Flight Center 2000-06-01 2021-09-01 -180, -90, 180, 90 False climate, geophysical, gpm, imerg, jaxa, monthly, nasa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GPM_L3_IMERG_MONTHLY_V06.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GPM_L3_IMERG_MONTHLY_V06 proprietary NASA/GPM_L3/IMERG_MONTHLY_V07 GPM: Monthly Global Precipitation Measurement (GPM) vRelease 07 image_collection ee.ImageCollection('NASA/GPM_L3/IMERG_MONTHLY_V07') NASA GES DISC at NASA Goddard Space Flight Center 2000-06-01 2024-06-01 -180, -90, 180, 90 False climate, geophysical, gpm, imerg, jaxa, monthly, nasa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GPM_L3_IMERG_MONTHLY_V07.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GPM_L3_IMERG_MONTHLY_V07 proprietary NASA/GPM_L3/IMERG_V06 GPM: Global Precipitation Measurement (GPM) Release 06 [deprecated] image_collection ee.ImageCollection('NASA/GPM_L3/IMERG_V06') NASA GES DISC at NASA Goddard Space Flight Center 2000-06-01 2024-06-02 -180, -90, 180, 90 True climate, geophysical, gpm, half_hourly, imerg, jaxa, nasa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GPM_L3_IMERG_V06.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GPM_L3_IMERG_V06 proprietary -NASA/GPM_L3/IMERG_V07 GPM: Global Precipitation Measurement (GPM) Release 07 image_collection ee.ImageCollection('NASA/GPM_L3/IMERG_V07') NASA GES DISC at NASA Goddard Space Flight Center 2000-06-01 2024-11-11 -180, -90, 180, 90 False climate, geophysical, gpm, half_hourly, imerg, jaxa, nasa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GPM_L3_IMERG_V07.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GPM_L3_IMERG_V07 proprietary +NASA/GPM_L3/IMERG_V07 GPM: Global Precipitation Measurement (GPM) Release 07 image_collection ee.ImageCollection('NASA/GPM_L3/IMERG_V07') NASA GES DISC at NASA Goddard Space Flight Center 2000-06-01 2024-11-12 -180, -90, 180, 90 False climate, geophysical, gpm, half_hourly, imerg, jaxa, nasa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GPM_L3_IMERG_V07.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GPM_L3_IMERG_V07 proprietary NASA/GRACE/MASS_GRIDS/LAND GRACE Monthly Mass Grids - Land [deprecated] image_collection ee.ImageCollection('NASA/GRACE/MASS_GRIDS/LAND') NASA Jet Propulsion Laboratory 2002-04-01 2017-01-07 -180, -90, 180, 90 True crs, gfz, grace, gravity, jpl, land, mass, nasa, tellus, water https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GRACE_MASS_GRIDS_LAND.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GRACE_MASS_GRIDS_LAND proprietary NASA/GRACE/MASS_GRIDS/MASCON GRACE Monthly Mass Grids - Global Mascons [deprecated] image_collection ee.ImageCollection('NASA/GRACE/MASS_GRIDS/MASCON') NASA Jet Propulsion Laboratory 2002-03-31 2017-05-22 -180, -90, 180, 90 True grace, gravity, jpl, mascon, mass, nasa, tellus, water https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GRACE_MASS_GRIDS_MASCON.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GRACE_MASS_GRIDS_MASCON proprietary NASA/GRACE/MASS_GRIDS/MASCON_CRI GRACE Monthly Mass Grids - Global Mascon (CRI Filtered) [deprecated] image_collection ee.ImageCollection('NASA/GRACE/MASS_GRIDS/MASCON_CRI') NASA Jet Propulsion Laboratory 2002-03-31 2017-05-22 -180, -90, 180, 90 True grace, gravity, jpl, mascon, mass, nasa, tellus, water https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GRACE_MASS_GRIDS_MASCON_CRI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GRACE_MASS_GRIDS_MASCON_CRI proprietary @@ -572,14 +572,14 @@ NASA/GSFC/MERRA/rad/2 MERRA-2 M2T1NXRAD: Radiation Diagnostics V5.12.4 image_col NASA/GSFC/MERRA/slv/2 MERRA-2 M2T1NXSLV: Single-Level Diagnostics V5.12.4 image_collection ee.ImageCollection('NASA/GSFC/MERRA/slv/2') NASA/MERRA 1980-01-01 2024-10-01 -180, -90, 180, 90 False condensation, humidity, merra, nasa, omega, pressure, slv, temperature, vapor, water, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_GSFC_MERRA_slv_2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_GSFC_MERRA_slv_2 proprietary NASA/HLS/HLSL30/v002 HLSL30: HLS-2 Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m image_collection ee.ImageCollection('NASA/HLS/HLSL30/v002') NASA LP DAAC 2013-04-11 2024-11-09 -180, -90, 180, 90 False landsat, nasa, sentinel, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_HLS_HLSL30_v002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_HLS_HLSL30_v002 proprietary NASA/JPL/global_forest_canopy_height_2005 Global Forest Canopy Height, 2005 image ee.Image('NASA/JPL/global_forest_canopy_height_2005') NASA/JPL 2005-05-20 2005-06-23 -180, -90, 180, 90 False canopy, forest, geophysical, glas, jpl, nasa https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_JPL_global_forest_canopy_height_2005.json https://developers.google.com/earth-engine/datasets/catalog/NASA_JPL_global_forest_canopy_height_2005 proprietary -NASA/LANCE/NOAA20_VIIRS/C2 VJ114IMGTDL_NRT Daily Raster: VIIRS (NOAA-20) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2') NASA / LANCE / NOAA20_VIIRS 2023-10-08 2024-11-10 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_NOAA20_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_NOAA20_VIIRS_C2 proprietary -NASA/LANCE/SNPP_VIIRS/C2 VNP14IMGTDL_NRT Daily Raster: VIIRS (S-NPP) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2') NASA / LANCE / SNPP_VIIRS 2023-09-03 2024-11-10 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_SNPP_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_SNPP_VIIRS_C2 proprietary +NASA/LANCE/NOAA20_VIIRS/C2 VJ114IMGTDL_NRT Daily Raster: VIIRS (NOAA-20) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/NOAA20_VIIRS/C2') NASA / LANCE / NOAA20_VIIRS 2023-10-08 2024-11-11 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_NOAA20_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_NOAA20_VIIRS_C2 proprietary +NASA/LANCE/SNPP_VIIRS/C2 VNP14IMGTDL_NRT Daily Raster: VIIRS (S-NPP) Band 375m Active Fire image_collection ee.ImageCollection('NASA/LANCE/SNPP_VIIRS/C2') NASA / LANCE / SNPP_VIIRS 2023-09-03 2024-11-11 -180, -90, 180, 90 False eosdis, fire, firms, geophysical, hotspot, lance, modis, nasa, thermal, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_LANCE_SNPP_VIIRS_C2.json https://developers.google.com/earth-engine/datasets/catalog/NASA_LANCE_SNPP_VIIRS_C2 proprietary NASA/MEASURES/GFCC/TC/v3 Global Forest Cover Change (GFCC) Tree Cover Multi-Year Global 30m image_collection ee.ImageCollection('NASA/MEASURES/GFCC/TC/v3') NASA LP DAAC at the USGS EROS Center 2000-01-01 2015-01-01 -180, -90, 180, 90 False forest, glcf, landsat_derived, nasa, umd https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_MEASURES_GFCC_TC_v3.json https://developers.google.com/earth-engine/datasets/catalog/NASA_MEASURES_GFCC_TC_v3 proprietary NASA/NASADEM_HGT/001 NASADEM: NASA NASADEM Digital Elevation 30m image ee.Image('NASA/NASADEM_HGT/001') NASA / USGS / JPL-Caltech 2000-02-11 2000-02-22 -180, -56, 180, 60 False dem, elevation, geophysical, nasa, nasadem, srtm, topography, usgs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NASADEM_HGT_001.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NASADEM_HGT_001 proprietary NASA/NEX-DCP30 NEX-DCP30: NASA Earth Exchange Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-DCP30') NASA / Climate Analytics Group 1950-01-01 2099-12-01 -125.03, 24.07, -66.47, 53.74 False cag, climate, cmip5, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-DCP30.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30 proprietary NASA/NEX-DCP30_ENSEMBLE_STATS NEX-DCP30: Ensemble Stats for NASA Earth Exchange Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-DCP30_ENSEMBLE_STATS') NASA / Climate Analytics Group 1950-01-01 2099-12-01 -125.03, 24.07, -66.47, 49.93 False cag, climate, cmip5, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-DCP30_ENSEMBLE_STATS.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30_ENSEMBLE_STATS proprietary NASA/NEX-GDDP NEX-GDDP: NASA Earth Exchange Global Daily Downscaled Climate Projections image_collection ee.ImageCollection('NASA/NEX-GDDP') NASA / Climate Analytics Group 1950-01-01 2100-12-31 -180, -90, 180, 90 False cag, climate, cmip5, gddp, geophysical, ipcc, nasa, nex, precipitation, temperature https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NEX-GDDP.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-GDDP proprietary -NASA/NLDAS/FORA0125_H002 NLDAS-2: North American Land Data Assimilation System Forcing Fields image_collection ee.ImageCollection('NASA/NLDAS/FORA0125_H002') NASA GES DISC at NASA Goddard Space Flight Center 1979-01-01 2024-11-08 -125.15, 24.85, -66.85, 53.28 False climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NLDAS_FORA0125_H002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NLDAS_FORA0125_H002 proprietary +NASA/NLDAS/FORA0125_H002 NLDAS-2: North American Land Data Assimilation System Forcing Fields image_collection ee.ImageCollection('NASA/NLDAS/FORA0125_H002') NASA GES DISC at NASA Goddard Space Flight Center 1979-01-01 2024-11-09 -125.15, 24.85, -66.85, 53.28 False climate, evaporation, forcing, geophysical, hourly, humidity, ldas, nasa, nldas, precipitation, pressure, radiation, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_NLDAS_FORA0125_H002.json https://developers.google.com/earth-engine/datasets/catalog/NASA_NLDAS_FORA0125_H002 proprietary NASA/OCEANDATA/MODIS-Aqua/L3SMI Ocean Color SMI: Standard Mapped Image MODIS Aqua Data image_collection ee.ImageCollection('NASA/OCEANDATA/MODIS-Aqua/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 2002-07-03 2022-02-28 -180, -90, 180, 90 False biology, chlorophyll, climate, modis, nasa, ocean, oceandata, reflectance, sst, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_MODIS-Aqua_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Aqua_L3SMI proprietary NASA/OCEANDATA/MODIS-Terra/L3SMI Ocean Color SMI: Standard Mapped Image MODIS Terra Data image_collection ee.ImageCollection('NASA/OCEANDATA/MODIS-Terra/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 2000-02-24 2022-02-28 -180, -90, 180, 90 False biology, chlorophyll, climate, modis, nasa, ocean, oceandata, reflectance, sst, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_MODIS-Terra_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Terra_L3SMI proprietary NASA/OCEANDATA/SeaWiFS/L3SMI Ocean Color SMI: Standard Mapped Image SeaWiFS Data image_collection ee.ImageCollection('NASA/OCEANDATA/SeaWiFS/L3SMI') NASA OB.DAAC at NASA Goddard Space Flight Center 1997-09-04 2010-12-10 -180, -90, 180, 90 False biology, chlorophyll, climate, nasa, ocean, oceandata, reflectance, seawifs, temperature, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_OCEANDATA_SeaWiFS_L3SMI.json https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_SeaWiFS_L3SMI proprietary @@ -588,8 +588,8 @@ NASA/ORNL/DAYMET_V4 Daymet V4: Daily Surface Weather and Climatological Summarie NASA/ORNL/biomass_carbon_density/v1 Global Aboveground and Belowground Biomass Carbon Density Maps image_collection ee.ImageCollection('NASA/ORNL/biomass_carbon_density/v1') NASA ORNL DAAC at Oak Ridge National Laboratory 2010-01-01 2010-12-31 -180, -61.1, 180, 84 False aboveground, belowground, biomass, carbon, density, forest, nasa, ornl, vegetation https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_ORNL_biomass_carbon_density_v1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_ORNL_biomass_carbon_density_v1 proprietary NASA/ORNL/global_forest_classification_2020/V1 Global 2020 Forest Classification for IPCC Aboveground Biomass Tier 1 Estimates, V1 image_collection ee.ImageCollection('NASA/ORNL/global_forest_classification_2020/V1') NASA ORNL DAAC at Oak Ridge National Laboratory 2020-01-01 2020-12-31 -180, -90, 180, 90 False aboveground, biomass, carbon, classification, forest, ipcc, nasa, primary_forest, secondary_forest https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_ORNL_global_forest_classification_2020_V1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_ORNL_global_forest_classification_2020_V1 proprietary NASA/SMAP/SPL3SMP_E/005 SPL3SMP_E.005 SMAP L3 Radiometer Global Daily 9 km Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL3SMP_E/005') Google and NSIDC 2015-03-31 2023-12-03 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL3SMP_E_005.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL3SMP_E_005 proprietary -NASA/SMAP/SPL3SMP_E/006 SPL3SMP_E.006 SMAP L3 Radiometer Global Daily 9 km Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL3SMP_E/006') Google and NSIDC 2023-12-04 2024-11-09 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL3SMP_E_006.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL3SMP_E_006 proprietary -NASA/SMAP/SPL4SMGP/007 SPL4SMGP.007 SMAP L4 Global 3-hourly 9-km Surface and Root Zone Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL4SMGP/007') Google and NSIDC 2015-03-31 2024-11-06 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL4SMGP_007.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL4SMGP_007 proprietary +NASA/SMAP/SPL3SMP_E/006 SPL3SMP_E.006 SMAP L3 Radiometer Global Daily 9 km Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL3SMP_E/006') Google and NSIDC 2023-12-04 2024-11-11 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL3SMP_E_006.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL3SMP_E_006 proprietary +NASA/SMAP/SPL4SMGP/007 SPL4SMGP.007 SMAP L4 Global 3-hourly 9-km Surface and Root Zone Soil Moisture image_collection ee.ImageCollection('NASA/SMAP/SPL4SMGP/007') Google and NSIDC 2015-03-31 2024-11-10 -180, -84, 180, 84 False drought, nasa, smap, soil_moisture, surface, weather https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_SMAP_SPL4SMGP_007.json https://developers.google.com/earth-engine/datasets/catalog/NASA_SMAP_SPL4SMGP_007 proprietary NASA/VIIRS/002/VNP09GA VNP09GA: VIIRS Surface Reflectance Daily 500m and 1km image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09GA') NASA Land SIPS 2012-01-19 2024-11-06 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09GA.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09GA proprietary NASA/VIIRS/002/VNP09H1 VNP09H1: VIIRS Surface Reflectance 8-Day L3 Global 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP09H1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-10-23 -180, -90, 180, 90 False daily, nasa, noaa, npp, reflectance, sr, viirs https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP09H1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP09H1 proprietary NASA/VIIRS/002/VNP13A1 VNP13A1.002: VIIRS Vegetation Indices 16-Day 500m image_collection ee.ImageCollection('NASA/VIIRS/002/VNP13A1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-10-15 -180, -90, 180, 90 False 16_day, evi, nasa, ndvi, noaa, npp, vegetation, viirs, vnp13a1 https://storage.googleapis.com/earthengine-stac/catalog/NASA/NASA_VIIRS_002_VNP13A1.json https://developers.google.com/earth-engine/datasets/catalog/NASA_VIIRS_002_VNP13A1 proprietary @@ -600,9 +600,9 @@ NASA/VIIRS/002/VNP21A1N VNP21A1N.002: Night Land Surface Temperature and Emissiv NASA_USDA/HSL/SMAP10KM_soil_moisture NASA-USDA Enhanced SMAP Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/SMAP10KM_soil_moisture') NASA GSFC 2015-04-02 2022-08-02 -180, -60, 180, 90 True geophysical, hsl, nasa, smap, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_SMAP10KM_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_SMAP10KM_soil_moisture proprietary NASA_USDA/HSL/SMAP_soil_moisture NASA-USDA SMAP Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/SMAP_soil_moisture') NASA GSFC 2015-04-02 2020-12-31 -180, -60, 180, 90 True geophysical, hsl, nasa, smap, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_SMAP_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_SMAP_soil_moisture proprietary NASA_USDA/HSL/soil_moisture NASA-USDA Global Soil Moisture Data [deprecated] image_collection ee.ImageCollection('NASA_USDA/HSL/soil_moisture') NASA GSFC 2010-01-13 2020-12-31 -180, -60, 180, 90 True geophysical, hsl, nasa, smos, soil, soil_moisture, usda https://storage.googleapis.com/earthengine-stac/catalog/NASA_USDA/NASA_USDA_HSL_soil_moisture.json https://developers.google.com/earth-engine/datasets/catalog/NASA_USDA_HSL_soil_moisture proprietary -NCEP_RE/sea_level_pressure NCEP/NCAR Reanalysis Data, Sea-Level Pressure image_collection ee.ImageCollection('NCEP_RE/sea_level_pressure') NCEP 1948-01-01 2024-11-08 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, pressure, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_sea_level_pressure.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_sea_level_pressure proprietary -NCEP_RE/surface_temp NCEP/NCAR Reanalysis Data, Surface Temperature image_collection ee.ImageCollection('NCEP_RE/surface_temp') NCEP 1948-01-01 2024-11-08 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_temp.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_temp proprietary -NCEP_RE/surface_wv NCEP/NCAR Reanalysis Data, Water Vapor image_collection ee.ImageCollection('NCEP_RE/surface_wv') NCEP 1948-01-01 2024-11-08 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, precipitable, reanalysis, vapor https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_wv.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_wv proprietary +NCEP_RE/sea_level_pressure NCEP/NCAR Reanalysis Data, Sea-Level Pressure image_collection ee.ImageCollection('NCEP_RE/sea_level_pressure') NCEP 1948-01-01 2024-11-09 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, pressure, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_sea_level_pressure.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_sea_level_pressure proprietary +NCEP_RE/surface_temp NCEP/NCAR Reanalysis Data, Surface Temperature image_collection ee.ImageCollection('NCEP_RE/surface_temp') NCEP 1948-01-01 2024-11-09 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, reanalysis, temperature https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_temp.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_temp proprietary +NCEP_RE/surface_wv NCEP/NCAR Reanalysis Data, Water Vapor image_collection ee.ImageCollection('NCEP_RE/surface_wv') NCEP 1948-01-01 2024-11-09 -180, -90, 180, 90 False atmosphere, climate, geophysical, ncep, noaa, precipitable, reanalysis, vapor https://storage.googleapis.com/earthengine-stac/catalog/NCEP_RE/NCEP_RE_surface_wv.json https://developers.google.com/earth-engine/datasets/catalog/NCEP_RE_surface_wv proprietary NOAA/CDR/ATMOS_NEAR_SURFACE/V2 NOAA CDR: Ocean Near-Surface Atmospheric Properties, Version 2 image_collection ee.ImageCollection('NOAA/CDR/ATMOS_NEAR_SURFACE/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False air_temperature, atmospheric, cdr, hourly, humidity, noaa, ocean, osb, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_ATMOS_NEAR_SURFACE_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_ATMOS_NEAR_SURFACE_V2 proprietary NOAA/CDR/AVHRR/AOT/V3 NOAA CDR AVHRR AOT: Daily Aerosol Optical Thickness Over Global Oceans, v03 [deprecated] image_collection ee.ImageCollection('NOAA/CDR/AVHRR/AOT/V3') NOAA 1981-01-01 2022-03-31 -180, -90, 180, 90 True aerosol, aot, atmospheric, avhrr, cdr, daily, noaa, optical, pollution https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_AVHRR_AOT_V3.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_AVHRR_AOT_V3 proprietary NOAA/CDR/AVHRR/AOT/V4 NOAA CDR AVHRR AOT: Daily Aerosol Optical Thickness Over Global Oceans, v04 image_collection ee.ImageCollection('NOAA/CDR/AVHRR/AOT/V4') NOAA 1981-01-01 2024-06-30 -180, -90, 180, 90 False aerosol, aot, atmospheric, avhrr, cdr, daily, noaa, optical, pollution https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_AVHRR_AOT_V4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_AVHRR_AOT_V4 proprietary @@ -615,38 +615,38 @@ NOAA/CDR/AVHRR/SR/V5 NOAA CDR AVHRR: Surface Reflectance, Version 5 image_collec NOAA/CDR/GRIDSAT-B1/V2 NOAA CDR GRIDSAT-B1: Geostationary IR Channel Brightness Temperature image_collection ee.ImageCollection('NOAA/CDR/GRIDSAT-B1/V2') NOAA 1980-01-01 2024-03-31 -180, -90, 180, 90 False brightness, cdr, fundamental, geostationary, infrared, isccp, noaa, reflectance, sr https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_GRIDSAT-B1_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_GRIDSAT-B1_V2 proprietary NOAA/CDR/HEAT_FLUXES/V2 NOAA CDR: Ocean Heat Fluxes, Version 2 image_collection ee.ImageCollection('NOAA/CDR/HEAT_FLUXES/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False atmospheric, cdr, flux, heat, hourly, noaa, ocean, osb https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_HEAT_FLUXES_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_HEAT_FLUXES_V2 proprietary NOAA/CDR/OISST/V2 NOAA CDR OISST v2: Optimum Interpolation Sea Surface Temperature [deprecated] image_collection ee.ImageCollection('NOAA/CDR/OISST/V2') NOAA 1981-09-01 2020-04-26 -180, -90, 180, 90 True avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2 proprietary -NOAA/CDR/OISST/V2_1 NOAA CDR OISST v02r01: Optimum Interpolation Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/OISST/V2_1') NOAA 1981-09-01 2024-11-09 -180, -90, 180, 90 False avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2_1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2_1 proprietary +NOAA/CDR/OISST/V2_1 NOAA CDR OISST v02r01: Optimum Interpolation Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/OISST/V2_1') NOAA 1981-09-01 2024-11-10 -180, -90, 180, 90 False avhrr, cdr, daily, ice, noaa, ocean, oisst, real_time, sst, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_OISST_V2_1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_OISST_V2_1 proprietary NOAA/CDR/PATMOSX/V53 NOAA CDR PATMOSX: Cloud Properties, Reflectance, and Brightness Temperatures, Version 5.3 image_collection ee.ImageCollection('NOAA/CDR/PATMOSX/V53') NOAA 1979-01-01 2022-01-01 -180, -90, 180, 90 False atmospheric, avhrr, brightness, cdr, cloud, metop, noaa, optical, poes, reflectance, temperature https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_PATMOSX_V53.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_PATMOSX_V53 proprietary NOAA/CDR/SST_PATHFINDER/V53 NOAA AVHRR Pathfinder Version 5.3 Collated Global 4km Sea Surface Temperature image_collection ee.ImageCollection('NOAA/CDR/SST_PATHFINDER/V53') NOAA 1981-08-24 2023-12-30 -180, -90, 180, 90 False avhrr, noaa, pathfinder, sea_ice, sst, temperature, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_SST_PATHFINDER_V53.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_SST_PATHFINDER_V53 proprietary NOAA/CDR/SST_WHOI/V2 NOAA CDR WHOI: Sea Surface Temperature, Version 2 image_collection ee.ImageCollection('NOAA/CDR/SST_WHOI/V2') NOAA 1988-01-01 2021-08-31 -180, -90, 180, 90 False atmospheric, cdr, hourly, noaa, ocean, oisst, osb, sst, whoi https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CDR_SST_WHOI_V2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CDR_SST_WHOI_V2 proprietary -NOAA/CFSR CFSR: Climate Forecast System Reanalysis image_collection ee.ImageCollection('NOAA/CFSR') NOAA NWS National Centers for Environmental Prediction (NCEP) 2018-12-13 2024-11-11 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSR proprietary +NOAA/CFSR CFSR: Climate Forecast System Reanalysis image_collection ee.ImageCollection('NOAA/CFSR') NOAA NWS National Centers for Environmental Prediction (NCEP) 2018-12-13 2024-11-12 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSR proprietary NOAA/CFSV2/FOR6H CFSV2: NCEP Climate Forecast System Version 2, 6-Hourly Products image_collection ee.ImageCollection('NOAA/CFSV2/FOR6H') NOAA NWS National Centers for Environmental Prediction (NCEP) 1979-01-01 2024-11-11 -180, -90, 180, 90 False climate, daylight, flux, forecast, geophysical, ncep, noaa, nws, precipitation, radiation, snow, temperature, vapor, water, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CFSV2_FOR6H.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CFSV2_FOR6H proprietary -NOAA/CPC/Precipitation CPC Global Unified Gauge-Based Analysis of Daily Precipitation image_collection ee.ImageCollection('NOAA/CPC/Precipitation') NOAA Physical Sciences Laboratory 2006-01-01 2024-11-09 -180, -90, 180, 90 False daily, noaa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CPC_Precipitation.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CPC_Precipitation proprietary -NOAA/CPC/Temperature CPC Global Unified Temperature image_collection ee.ImageCollection('NOAA/CPC/Temperature') NOAA Physical Sciences Laboratory 1979-01-01 2024-11-10 -180, -90, 180, 90 False daily, noaa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CPC_Temperature.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CPC_Temperature proprietary +NOAA/CPC/Precipitation CPC Global Unified Gauge-Based Analysis of Daily Precipitation image_collection ee.ImageCollection('NOAA/CPC/Precipitation') NOAA Physical Sciences Laboratory 2006-01-01 2024-11-10 -180, -90, 180, 90 False daily, noaa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CPC_Precipitation.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CPC_Precipitation proprietary +NOAA/CPC/Temperature CPC Global Unified Temperature image_collection ee.ImageCollection('NOAA/CPC/Temperature') NOAA Physical Sciences Laboratory 1979-01-01 2024-11-11 -180, -90, 180, 90 False daily, noaa, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_CPC_Temperature.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_CPC_Temperature proprietary NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4 DMSP OLS: Global Radiance-Calibrated Nighttime Lights Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1996-03-16 2011-07-31 -180, -65, 180, 75 False calibrated, dmsp, eog, imagery, lights, nighttime, ols, radiance, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_CALIBRATED_LIGHTS_V4 proprietary NOAA/DMSP-OLS/NIGHTTIME_LIGHTS DMSP OLS: Nighttime Lights Time Series Version 4, Defense Meteorological Program Operational Linescan System image_collection ee.ImageCollection('NOAA/DMSP-OLS/NIGHTTIME_LIGHTS') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 1992-01-01 2014-01-01 -180, -65, 180, 75 False dmsp, eog, imagery, lights, nighttime, ols, visible, yearly https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_DMSP-OLS_NIGHTTIME_LIGHTS proprietary -NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2024-11-11 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary -NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2024-11-11 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary -NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2024-11-11 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary -NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2024-11-11 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary -NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2024-11-11 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary -NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2024-11-11 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary +NOAA/GFS0P25 GFS: Global Forecast System 384-Hour Predicted Atmosphere Data image_collection ee.ImageCollection('NOAA/GFS0P25') NOAA/NCEP/EMC 2015-07-01 2024-11-12 -180, -90, 180, 90 False climate, cloud, emc, flux, forecast, geophysical, gfs, humidity, ncep, noaa, precipitation, radiation, temperature, vapor, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GFS0P25.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25 proprietary +NOAA/GOES/16/FDCC GOES-16 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/16/FDCC') NOAA 2017-05-24 2024-11-12 -152.11, 14, -49.18, 56.77 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCC proprietary +NOAA/GOES/16/FDCF GOES-16 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/FDCF') NOAA 2017-05-24 2024-11-12 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_16, goes_east, goes_r, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_FDCF proprietary +NOAA/GOES/16/MCMIPC GOES-16 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPC') NOAA 2017-07-10 2024-11-12 -152.11, 14, -49.18, 56.77 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPC proprietary +NOAA/GOES/16/MCMIPF GOES-16 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPF') NOAA 2017-07-10 2024-11-12 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF proprietary +NOAA/GOES/16/MCMIPM GOES-16 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Mesoscale image_collection ee.ImageCollection('NOAA/GOES/16/MCMIPM') NOAA 2017-07-10 2024-11-12 -180, -90, 180, 90 False abi, climate, goes, goes_16, goes_east, goes_r, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_16_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPM proprietary NOAA/GOES/17/FDCC GOES-17 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/17/FDCC') NOAA 2018-08-27 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCC proprietary NOAA/GOES/17/FDCF GOES-17 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/FDCF') NOAA 2018-08-27 2023-01-10 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_17, goes_s, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_FDCF proprietary NOAA/GOES/17/MCMIPC GOES-17 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPC') NOAA 2018-12-04 2023-01-10 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPC proprietary NOAA/GOES/17/MCMIPF GOES-17 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPF') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPF proprietary NOAA/GOES/17/MCMIPM GOES-17 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/17/MCMIPM') NOAA 2018-12-04 2023-01-10 -180, -90, 180, 90 False abi, climate, goes, goes_17, goes_s, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_17_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_17_MCMIPM proprietary -NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2024-11-11 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary -NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2024-11-11 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary -NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2024-11-11 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary -NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2024-11-11 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary -NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2024-11-11 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary +NOAA/GOES/18/FDCC GOES-18 FDCC Series ABI Level 2 Fire/Hot Spot Characterization CONUS image_collection ee.ImageCollection('NOAA/GOES/18/FDCC') NOAA 2022-10-13 2024-11-12 -180, 14.57, 180, 53.51 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCC proprietary +NOAA/GOES/18/FDCF GOES-18 FDCF Series ABI Level 2 Fire/Hot Spot Characterization Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/FDCF') NOAA 2022-10-13 2024-11-12 -180, -90, 180, 90 False abi, climate, fdc, fire, goes, goes_18, goes_t, goes_west, hotspot, nesdis, noaa, ospo, wildfire https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_FDCF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_FDCF proprietary +NOAA/GOES/18/MCMIPC GOES-18 MCMIPC Series ABI Level 2 Cloud and Moisture Imagery CONUS image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPC') NOAA 2018-12-04 2024-11-12 -180, 14.57, 180, 53.51 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPC.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPC proprietary +NOAA/GOES/18/MCMIPF GOES-18 MCMIPF Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPF') NOAA 2018-12-04 2024-11-12 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPF.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPF proprietary +NOAA/GOES/18/MCMIPM GOES-18 MCMIPM Series ABI Level 2 Cloud and Moisture Imagery Full Disk image_collection ee.ImageCollection('NOAA/GOES/18/MCMIPM') NOAA 2018-12-04 2024-11-12 -180, -90, 180, 90 False abi, climate, goes, goes_18, goes_t, goes_west, mcmip, nesdis, noaa, ospo, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_GOES_18_MCMIPM.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_18_MCMIPM proprietary NOAA/IBTrACS/v4 International Best Track Archive for Climate Stewardship Project table ee.FeatureCollection('NOAA/IBTrACS/v4') NOAA NCEI 1842-10-25 2024-05-19 -180, 0.4, 180, 63.1 False hurricane, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_IBTrACS_v4.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_IBTrACS_v4 proprietary NOAA/NCEP_DOE_RE2/total_cloud_coverage NCEP-DOE Reanalysis 2 (Gaussian Grid), Total Cloud Coverage image_collection ee.ImageCollection('NOAA/NCEP_DOE_RE2/total_cloud_coverage') NOAA 1979-01-01 2024-10-31 -180, -90, 180, 90 False atmosphere, climate, cloud, geophysical, ncep, noaa, reanalysis https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NCEP_DOE_RE2_total_cloud_coverage.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NCEP_DOE_RE2_total_cloud_coverage proprietary NOAA/NGDC/ETOPO1 ETOPO1: Global 1 Arc-Minute Elevation image ee.Image('NOAA/NGDC/ETOPO1') NOAA 2008-08-01 2008-08-01 -180, -90, 180, 90 False bedrock, dem, elevation, geophysical, ice, noaa, topography https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NGDC_ETOPO1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NGDC_ETOPO1 proprietary NOAA/NHC/HURDAT2/atlantic NOAA NHC HURDAT2 Atlantic Hurricane Catalog table ee.FeatureCollection('NOAA/NHC/HURDAT2/atlantic') NOAA NHC 1851-06-25 2018-11-04 -109.5, 7.2, 63, 81 False hurricane, nhc, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NHC_HURDAT2_atlantic.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NHC_HURDAT2_atlantic proprietary NOAA/NHC/HURDAT2/pacific NOAA NHC HURDAT2 Pacific Hurricane Catalog table ee.FeatureCollection('NOAA/NHC/HURDAT2/pacific') NOAA NHC 1949-06-11 2018-11-09 -180, 0.4, 180, 63.1 False hurricane, nhc, noaa, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NHC_HURDAT2_pacific.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NHC_HURDAT2_pacific proprietary -NOAA/NWS/RTMA RTMA: Real-Time Mesoscale Analysis image_collection ee.ImageCollection('NOAA/NWS/RTMA') NOAA/NWS 2011-01-01 2024-11-11 -130.17, 20.15, -60.81, 52.91 False climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NWS_RTMA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NWS_RTMA proprietary +NOAA/NWS/RTMA RTMA: Real-Time Mesoscale Analysis image_collection ee.ImageCollection('NOAA/NWS/RTMA') NOAA/NWS 2011-01-01 2024-11-12 -130.17, 20.15, -60.81, 52.91 False climate, cloud, geophysical, humidity, noaa, nws, precipitation, pressure, rtma, surface, temperature, visibility, weather, wind https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_NWS_RTMA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_NWS_RTMA proprietary NOAA/PERSIANN-CDR PERSIANN-CDR: Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record image_collection ee.ImageCollection('NOAA/PERSIANN-CDR') NOAA NCDC 1983-01-01 2024-03-31 -180, -60, 180, 60 False cdr, climate, geophysical, ncdc, noaa, persiann, precipitation, weather https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_PERSIANN-CDR.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_PERSIANN-CDR proprietary NOAA/VIIRS/001/VNP09GA VNP09GA: VIIRS Surface Reflectance Daily 500m and 1km [deprecated] image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP09GA') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-06-16 -180, -90, 180, 90 True daily, nasa, noaa, npp, reflectance, sr, viirs, vnp09ga https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP09GA.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP09GA proprietary NOAA/VIIRS/001/VNP09H1 VNP09H1: VIIRS Surface Reflectance 8-Day L3 Global 500m [deprecated] image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP09H1') NASA LP DAAC at the USGS EROS Center 2012-01-19 2024-06-09 -180, -90, 180, 90 True daily, nasa, noaa, npp, reflectance, sr, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP09H1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP09H1 proprietary @@ -659,7 +659,7 @@ NOAA/VIIRS/001/VNP22Q2 VNP22Q2: Land Surface Phenology Yearly L3 Global 500m SIN NOAA/VIIRS/001/VNP43IA1 VNP43IA1: BRDF/Albedo Model Parameters Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA1') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-06-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA1 proprietary NOAA/VIIRS/001/VNP43IA2 VNP43IA2: BRDF/Albedo Quality Daily L3 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP43IA2') NASA LP DAAC at the USGS EROS Center 2012-01-17 2024-06-09 -180, -90, 180, 90 False land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP43IA2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP43IA2 proprietary NOAA/VIIRS/001/VNP46A1 VNP46A1: VIIRS Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A1') NASA LAADS DAAC 2012-01-19 2024-11-08 -180, -90, 180, 90 False daily, dnb, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A1 proprietary -NOAA/VIIRS/001/VNP46A2 VNP46A2: VIIRS Lunar Gap-Filled BRDF Nighttime Lights Daily L3 Global 500m image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A2') NASA LAADS DAAC 2012-01-19 2024-10-26 -180, -90, 180, 90 False brdf, daily, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A2 proprietary +NOAA/VIIRS/001/VNP46A2 VNP46A2: VIIRS Lunar Gap-Filled BRDF Nighttime Lights Daily L3 Global 500m image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP46A2') NASA LAADS DAAC 2012-01-19 2024-10-27 -180, -90, 180, 90 False brdf, daily, nasa, noaa, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP46A2.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP46A2 proprietary NOAA/VIIRS/001/VNP64A1 VNP64A1: Burned Area Monthly L4 Global 500m SIN Grid image_collection ee.ImageCollection('NOAA/VIIRS/001/VNP64A1') NASA LP DAAC at the USGS EROS Center 2014-01-01 2019-01-01 -180, -90, 180, 90 False burn, change_detection, land, nasa, noaa, surface, viirs https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_001_VNP64A1.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_001_VNP64A1 proprietary NOAA/VIIRS/DNB/ANNUAL_V21 VIIRS Nighttime Day/Night Annual Band Composites V2.1 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/ANNUAL_V21') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2012-04-01 2021-01-01 -180, -65, 180, 75 False annual, dnb, eog, lights, nighttime, noaa, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_ANNUAL_V21.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V21 proprietary NOAA/VIIRS/DNB/ANNUAL_V22 VIIRS Nighttime Day/Night Annual Band Composites V2.2 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/ANNUAL_V22') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2012-04-01 2023-01-01 -180, -65, 180, 75 False annual, dnb, eog, lights, nighttime, noaa, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_ANNUAL_V22.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_ANNUAL_V22 proprietary @@ -667,7 +667,7 @@ NOAA/VIIRS/DNB/MONTHLY_V1/VCMCFG VIIRS Nighttime Day/Night Band Composites Versi NOAA/VIIRS/DNB/MONTHLY_V1/VCMSLCFG VIIRS Stray Light Corrected Nighttime Day/Night Band Composites Version 1 image_collection ee.ImageCollection('NOAA/VIIRS/DNB/MONTHLY_V1/VCMSLCFG') Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines 2014-01-01 2024-06-04 -180, -65, 180, 75 False dnb, eog, lights, monthly, nighttime, noaa, stray_light, viirs, visible https://storage.googleapis.com/earthengine-stac/catalog/NOAA/NOAA_VIIRS_DNB_MONTHLY_V1_VCMSLCFG.json https://developers.google.com/earth-engine/datasets/catalog/NOAA_VIIRS_DNB_MONTHLY_V1_VCMSLCFG proprietary NRCan/CDEM Canadian Digital Elevation Model image_collection ee.ImageCollection('NRCan/CDEM') NRCan 1945-01-01 2011-01-01 -142, 41, -52, 84 False canada, cdem, dem, elevation, geophysical, nrcan, topography https://storage.googleapis.com/earthengine-stac/catalog/NRCan/NRCan_CDEM.json https://developers.google.com/earth-engine/datasets/catalog/NRCan_CDEM OGL-Canada-2.0 Netherlands/Beeldmateriaal/LUCHTFOTO_RGB Netherlands orthophotos image_collection ee.ImageCollection('Netherlands/Beeldmateriaal/LUCHTFOTO_RGB') Beeldmateriaal Nederland 2021-01-01 2022-12-31 3.2, 50.75, 7.22, 53.7 False orthophoto, rgb, netherlands https://storage.googleapis.com/earthengine-stac/catalog/Netherlands/Netherlands_Beeldmateriaal_LUCHTFOTO_RGB.json https://developers.google.com/earth-engine/datasets/catalog/Netherlands_Beeldmateriaal_LUCHTFOTO_RGB CC-BY-4.0 -OREGONSTATE/PRISM/AN81d PRISM Daily Spatial Climate Dataset AN81d image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81d') PRISM / OREGONSTATE 1981-01-01 2024-11-08 -125, 24, -66, 50 False climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81d.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81d proprietary +OREGONSTATE/PRISM/AN81d PRISM Daily Spatial Climate Dataset AN81d image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81d') PRISM / OREGONSTATE 1981-01-01 2024-11-09 -125, 24, -66, 50 False climate, daily, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81d.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81d proprietary OREGONSTATE/PRISM/AN81m PRISM Monthly Spatial Climate Dataset AN81m image_collection ee.ImageCollection('OREGONSTATE/PRISM/AN81m') PRISM / OREGONSTATE 1895-01-01 2024-10-01 -125, 24, -66, 50 False climate, geophysical, monthly, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_AN81m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_AN81m proprietary OREGONSTATE/PRISM/Norm81m PRISM Long-Term Average Climate Dataset Norm81m [deprecated] image_collection ee.ImageCollection('OREGONSTATE/PRISM/Norm81m') PRISM / OREGONSTATE 1981-01-01 2010-12-31 -125, 24, -66, 50 True 30_year, climate, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_Norm81m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_Norm81m proprietary OREGONSTATE/PRISM/Norm91m PRISM Long-Term Average Climate Dataset Norm91m image_collection ee.ImageCollection('OREGONSTATE/PRISM/Norm91m') PRISM / OREGONSTATE 1991-01-01 2020-12-31 -125, 24, -66, 50 False 30_year, climate, geophysical, oregonstate, precipitation, pressure, prism, temperature, vapor, weather https://storage.googleapis.com/earthengine-stac/catalog/OREGONSTATE/OREGONSTATE_PRISM_Norm91m.json https://developers.google.com/earth-engine/datasets/catalog/OREGONSTATE_PRISM_Norm91m proprietary @@ -730,7 +730,7 @@ TIGER/2018/States TIGER: US Census States 2018 table ee.FeatureCollection('TIGER TIGER/2020/BG TIGER: US Census Block Groups (BG) 2020 table ee.FeatureCollection('TIGER/2020/BG') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_BG.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_BG proprietary TIGER/2020/TABBLOCK20 TIGER: 2020 Tabulation (Census) Block table ee.FeatureCollection('TIGER/2020/TABBLOCK20') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TABBLOCK20.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TABBLOCK20 proprietary TIGER/2020/TRACT TIGER: US Census Tracts table ee.FeatureCollection('TIGER/2020/TRACT') United States Census Bureau 2020-01-01 2020-01-02 -180, -14.69, -64.435, 71.567 False census, city, neighborhood, tiger, urban, us https://storage.googleapis.com/earthengine-stac/catalog/TIGER/TIGER_2020_TRACT.json https://developers.google.com/earth-engine/datasets/catalog/TIGER_2020_TRACT proprietary -TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2024-11-09 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary +TOMS/MERGED TOMS and OMI Merged Ozone Data image_collection ee.ImageCollection('TOMS/MERGED') NASA / GES DISC 1978-11-01 2024-11-10 -180, -90, 180, 90 False atmosphere, aura, climate, geophysical, ges_disc, goddard, nasa, omi, ozone, toms https://storage.googleapis.com/earthengine-stac/catalog/TOMS/TOMS_MERGED.json https://developers.google.com/earth-engine/datasets/catalog/TOMS_MERGED proprietary TRMM/3B42 TRMM 3B42: 3-Hourly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B42') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-31 -180, -50, 180, 50 False 3_hourly, climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B42.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B42 proprietary TRMM/3B43V7 TRMM 3B43: Monthly Precipitation Estimates image_collection ee.ImageCollection('TRMM/3B43V7') NASA GES DISC at NASA Goddard Space Flight Center 1998-01-01 2019-12-01 -180, -50, 180, 50 False climate, geophysical, jaxa, nasa, precipitation, rainfall, trmm, weather https://storage.googleapis.com/earthengine-stac/catalog/TRMM/TRMM_3B43V7.json https://developers.google.com/earth-engine/datasets/catalog/TRMM_3B43V7 proprietary TUBerlin/BigEarthNet/v1 TUBerlin/BigEarthNet/v1 image_collection ee.ImageCollection('TUBerlin/BigEarthNet/v1') BigEarthNet 2017-06-01 2018-05-31 -9, 36.9, 31.6, 68.1 False chip, copernicus, corine_derived, label, ml, sentinel, tile https://storage.googleapis.com/earthengine-stac/catalog/TUBerlin/TUBerlin_BigEarthNet_v1.json https://developers.google.com/earth-engine/datasets/catalog/TUBerlin_BigEarthNet_v1 proprietary @@ -822,7 +822,7 @@ USGS/WBD/2017/HUC06 HUC06: USGS Watershed Boundary Dataset of Basins table ee.Fe USGS/WBD/2017/HUC08 HUC08: USGS Watershed Boundary Dataset of Subbasins table ee.FeatureCollection('USGS/WBD/2017/HUC08') United States Geological Survey 2017-04-22 2017-04-23 -180, -14.69, 180, 71.567 False hydrology, usgs, water, watershed, wbd https://storage.googleapis.com/earthengine-stac/catalog/USGS/USGS_WBD_2017_HUC08.json https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC08 proprietary USGS/WBD/2017/HUC10 HUC10: USGS Watershed Boundary Dataset of Watersheds table ee.FeatureCollection('USGS/WBD/2017/HUC10') United States Geological Survey 2017-04-22 2017-04-23 -180, -14.69, 180, 71.567 False hydrology, usgs, water, watershed, wbd https://storage.googleapis.com/earthengine-stac/catalog/USGS/USGS_WBD_2017_HUC10.json https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC10 proprietary USGS/WBD/2017/HUC12 HUC12: USGS Watershed Boundary Dataset of Subwatersheds table ee.FeatureCollection('USGS/WBD/2017/HUC12') United States Geological Survey 2017-04-22 2017-04-23 -180, -14.69, 180, 71.567 False hydrology, usgs, water, watershed, wbd https://storage.googleapis.com/earthengine-stac/catalog/USGS/USGS_WBD_2017_HUC12.json https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC12 proprietary -UTOKYO/WTLAB/KBDI/v1 KBDI: Keetch-Byram Drought Index image_collection ee.ImageCollection('UTOKYO/WTLAB/KBDI/v1') Institute of Industrial Science, The University of Tokyo, Japan 2007-01-01 2024-11-10 60, -60, 180, 60 False drought, kbdi, lst_derived, rainfall, utokyo, wtlab https://storage.googleapis.com/earthengine-stac/catalog/UTOKYO/UTOKYO_WTLAB_KBDI_v1.json https://developers.google.com/earth-engine/datasets/catalog/UTOKYO_WTLAB_KBDI_v1 CC-BY-4.0 +UTOKYO/WTLAB/KBDI/v1 KBDI: Keetch-Byram Drought Index image_collection ee.ImageCollection('UTOKYO/WTLAB/KBDI/v1') Institute of Industrial Science, The University of Tokyo, Japan 2007-01-01 2024-11-11 60, -60, 180, 60 False drought, kbdi, lst_derived, rainfall, utokyo, wtlab https://storage.googleapis.com/earthengine-stac/catalog/UTOKYO/UTOKYO_WTLAB_KBDI_v1.json https://developers.google.com/earth-engine/datasets/catalog/UTOKYO_WTLAB_KBDI_v1 CC-BY-4.0 VITO/PROBAV/C1/S1_TOC_100M PROBA-V C1 Top Of Canopy Daily Synthesis 100m image_collection ee.ImageCollection('VITO/PROBAV/C1/S1_TOC_100M') Vito / ESA 2013-10-17 2021-10-31 -180, -90, 180, 90 False esa, multispectral, nir, proba, probav, swir, vito https://storage.googleapis.com/earthengine-stac/catalog/VITO/VITO_PROBAV_C1_S1_TOC_100M.json https://developers.google.com/earth-engine/datasets/catalog/VITO_PROBAV_C1_S1_TOC_100M proprietary VITO/PROBAV/C1/S1_TOC_333M PROBA-V C1 Top Of Canopy Daily Synthesis 333m image_collection ee.ImageCollection('VITO/PROBAV/C1/S1_TOC_333M') Vito / ESA 2013-10-17 2021-10-31 -180, -90, 180, 90 False esa, multispectral, nir, proba, probav, swir, vito https://storage.googleapis.com/earthengine-stac/catalog/VITO/VITO_PROBAV_C1_S1_TOC_333M.json https://developers.google.com/earth-engine/datasets/catalog/VITO_PROBAV_C1_S1_TOC_333M proprietary VITO/PROBAV/S1_TOC_100M PROBA-V C0 Top Of Canopy Daily Synthesis 100m [deprecated] image_collection ee.ImageCollection('VITO/PROBAV/S1_TOC_100M') Vito / ESA 2013-10-17 2016-12-14 -180, -90, 180, 90 True esa, multispectral, nir, proba, probav, swir, vito https://storage.googleapis.com/earthengine-stac/catalog/VITO/VITO_PROBAV_S1_TOC_100M.json https://developers.google.com/earth-engine/datasets/catalog/VITO_PROBAV_S1_TOC_100M proprietary diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index b5a980a..7fe2eb1 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -31514,26 +31514,26 @@ { "id": "ATL03_006", "title": "ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL03_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL03_006", "description": "This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.", "license": "proprietary" }, { "id": "ATL03_006", "title": "ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL03_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL03_006", "description": "This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.", "license": "proprietary" }, @@ -31553,26 +31553,26 @@ { "id": "ATL04_006", "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL04_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04_006", "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL04_006", "title": "ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL04_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL04_006", "description": "ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31618,26 +31618,26 @@ { "id": "ATL07_006", "title": "ATLAS/ICESat-2 L3A Sea Ice Height V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL07_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL07_006", "description": "The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL07_006", "title": "ATLAS/ICESat-2 L3A Sea Ice Height V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL07_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL07_006", "description": "The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31657,26 +31657,26 @@ { "id": "ATL08_006", "title": "ATLAS/ICESat-2 L3A Land and Vegetation Height V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL08_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL08_006", "description": "This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL08_006", "title": "ATLAS/ICESat-2 L3A Land and Vegetation Height V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL08_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL08_006", "description": "This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31696,26 +31696,26 @@ { "id": "ATL09_006", "title": "ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL09_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL09_006", "description": "This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL09_006", "title": "ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL09_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL09_006", "description": "This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31787,26 +31787,26 @@ { "id": "ATL12_006", "title": "ATLAS/ICESat-2 L3A Ocean Surface Height V006", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL12_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL12_006", "description": "This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, { "id": "ATL12_006", "title": "ATLAS/ICESat-2 L3A Ocean Surface Height V006", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL12_006", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL12_006", "description": "This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. 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The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.", "license": "proprietary" }, @@ -31852,104 +31852,104 @@ { "id": "ATL14_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.", "license": "proprietary" }, { "id": "ATL14_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. 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The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).", "license": "proprietary" }, { "id": "ATL14_004", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-01-01", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL14_004", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL14_004", "description": "This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).", "license": "proprietary" }, { "id": "ATL15_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL15_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL15_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. 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ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.", "license": "proprietary" }, { "id": "ATL15_003", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-03-29", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL15_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL15_003", "description": "ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.", "license": "proprietary" }, { "id": "ATL15_004", "title": "ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2019-01-01", "end_date": "", "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684532-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3159684532-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL15_004", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL15_004", "description": "This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). 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The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).", "license": "proprietary" }, @@ -32086,52 +32086,52 @@ { "id": "ATL22_003", "title": "ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL22_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL22_003", "description": "ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.", "license": "proprietary" }, { "id": "ATL22_003", "title": "ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-14", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL22_003", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL22_003", "description": "ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.", "license": "proprietary" }, { "id": "ATL23_001", "title": "ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL23_001", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL23_001", "description": "This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates.", "license": "proprietary" }, { "id": "ATL23_001", "title": "ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2018-10-13", "end_date": "", "bbox": "-180, -88, 180, 88", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL23_001", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/ATL23_001", "description": "This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates.", "license": "proprietary" }, @@ -48325,7 +48325,7 @@ "title": "CERES A-Train Integrated CALIPSO, CloudSat, CERES, and MODIS (CCCM) Merged Release D2", "catalog": "LARC_ASDC STAC Catalog", "state_date": "2006-07-01", - "end_date": "2011-04-30", + "end_date": "2017-12-31", "bbox": "180, -90, -180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3091018780-LARC_ASDC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3091018780-LARC_ASDC.html", @@ -51164,7 +51164,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2673736502-SEDAC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2673736502-SEDAC.html", "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_AQDH_PM25COM_US_1KM_1.00", - "description": "The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 \u00ef\u00bf\u00bdm (PM2.5) increases mortality and morbidity. PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019. Using Machine-Learning models (ML), combined with either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA) or Super-Learning (SL) and approximately 82 billion predictions across 20 years, hyperlocal super-learned PM2.5 components are now available for further research. The overall R-squared values of 10-fold cross validated models ranged from 0.910 to 0.970 on the training sets for these components, while on the test sets the R-squared values ranged from 0.860 to 0.960. Remarkable spatiotemporal intra-urban and inter-urban variabilities were found in PM2.5 components. The Coordinate Reference System (CRS) for predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components are \u00ef\u00bf\u00bdg/m^3. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python.", + "description": "The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 microgram per cubic meter (PM2.5) increases mortality and morbidity. PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019. Using Machine-Learning models (ML), combined with either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA) or Super-Learning (SL) and approximately 82 billion predictions across 20 years, hyperlocal super-learned PM2.5 components are now available for further research. The overall R-squared values of 10-fold cross validated models ranged from 0.910 to 0.970 on the training sets for these components, while on the test sets the R-squared values ranged from 0.860 to 0.960. Remarkable spatiotemporal intra-urban and inter-urban variabilities were found in PM2.5 components. The Coordinate Reference System (CRS) for predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components are microgram per cubic meter. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python.", "license": "proprietary" }, { @@ -51190,7 +51190,7 @@ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2673738199-SEDAC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2673738199-SEDAC.html", "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_AQDH_TRACE_US_1KM_1.00", - "description": "The Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of trace elements concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and a high resolution (1km x 1km grid cells) in non-urban areas, for the years 2000 to 2019. Particulate matter with an aerodynamic diameter of less than 2.5 \u00ef\u00bf\u00bdm (PM2.5) is a human silent killer of millions worldwide, and contains many trace elements (TEs). Understanding the relative toxicity is largely limited by the lack of data. In this work, ensembles of machine learning models were used to generate approximately 163 billion predictions estimating annual mean PM2.5 TEs, namely Bromine (Br), Calcium (Ca), Copper (Cu), Iron (Fe), Potassium (K), Nickel (Ni), Lead (Pb), Silicon (Si), Vanadium (V), and Zinc (Zn). The monitored data from approximately 600 locations were integrated with more than 160 predictors, such as time and location, satellite observations, composite predictors, meteorological covariates, and many novel land use variables using several machine learning algorithms and ensemble methods. Multiple machine-learning models were developed covering urban areas and non-urban areas. Their predictions were then ensembled using either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA), or Super-Learners. The overall best model R-squared values for the test sets ranged from 0.79 for Copper to 0.88 for Zinc in non-urban areas. In urban areas, the R-squared model values ranged from 0.80 for Copper to 0.88 for Zinc. The Coordinate Reference System (CRS) used in the predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components TEs are ng/m^3. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python.", + "description": "The Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of trace elements concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and a high resolution (1km x 1km grid cells) in non-urban areas, for the years 2000 to 2019. Particulate matter with an aerodynamic diameter of less than 2.5 microgram per cubic meter (PM2.5) is a human silent killer of millions worldwide, and contains many trace elements (TEs). Understanding the relative toxicity is largely limited by the lack of data. In this work, ensembles of machine learning models were used to generate approximately 163 billion predictions estimating annual mean PM2.5 TEs, namely Bromine (Br), Calcium (Ca), Copper (Cu), Iron (Fe), Potassium (K), Nickel (Ni), Lead (Pb), Silicon (Si), Vanadium (V), and Zinc (Zn). The monitored data from approximately 600 locations were integrated with more than 160 predictors, such as time and location, satellite observations, composite predictors, meteorological covariates, and many novel land use variables using several machine learning algorithms and ensemble methods. Multiple machine-learning models were developed covering urban areas and non-urban areas. Their predictions were then ensembled using either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA), or Super-Learners. The overall best model R-squared values for the test sets ranged from 0.79 for Copper to 0.88 for Zinc in non-urban areas. In urban areas, the R-squared model values ranged from 0.80 for Copper to 0.88 for Zinc. The Coordinate Reference System (CRS) used in the predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components TEs are nanograms per cubic meter. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python.", "license": "proprietary" }, { @@ -79991,52 +79991,52 @@ { "id": "GLAH01_033", "title": "GLAS/ICESat L1A Global Altimetry Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH01_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH01_033", "description": "Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH01_033", "title": "GLAS/ICESat L1A Global Altimetry Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH01_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH01_033", "description": "Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH02_033", "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH02_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH02_033", "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH02_033", "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH02_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH02_033", "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80147,52 +80147,52 @@ { "id": "GLAH07_033", "title": "GLAS/ICESat L1B Global Backscatter Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH07_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH07_033", "description": "GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH07_033", "title": "GLAS/ICESat L1B Global Backscatter Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH07_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH07_033", "description": "GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH08_033", "title": "GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH08_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH08_033", "description": "GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH08_033", "title": "GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH08_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH08_033", "description": "GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80225,26 +80225,26 @@ { "id": "GLAH10_033", "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", - "catalog": "NSIDC_CPRD STAC Catalog", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-09-25", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH10_033", "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", "license": "proprietary" }, { "id": "GLAH10_033", "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033", - "catalog": "NSIDC_ECS STAC Catalog", + "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-09-25", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH10_033", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH10_033", "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80274,19 +80274,6 @@ "description": "GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.", "license": "proprietary" }, - { - "id": "GLAH12_034", - "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034", - "catalog": "NSIDC_ECS STAC Catalog", - "state_date": "2003-02-20", - "end_date": "2009-10-11", - "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH12_034", - "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", - "license": "proprietary" - }, { "id": "GLAH12_034", "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034", @@ -80301,15 +80288,15 @@ "license": "proprietary" }, { - "id": "GLAH13_034", - "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", - "catalog": "NSIDC_CPRD STAC Catalog", + "id": "GLAH12_034", + "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034", + "catalog": "NSIDC_ECS STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/GLAH12_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80327,15 +80314,15 @@ "license": "proprietary" }, { - "id": "GLAH14_034", - "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034", + "id": "GLAH13_034", + "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034", "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH14_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH13_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80353,15 +80340,15 @@ "license": "proprietary" }, { - "id": "GLAH15_034", - "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034", + "id": "GLAH14_034", + "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034", "catalog": "NSIDC_CPRD STAC Catalog", "state_date": "2003-02-20", "end_date": "2009-10-11", "bbox": "-180, -86, 180, 86", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH15_034", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH14_034", "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, @@ -80378,6 +80365,19 @@ "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", "license": "proprietary" }, + { + "id": "GLAH15_034", + "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034", + "catalog": "NSIDC_CPRD STAC Catalog", + "state_date": "2003-02-20", + "end_date": "2009-10-11", + "bbox": "-180, -86, 180, 86", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/GLAH15_034", + "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.", + "license": "proprietary" + }, { "id": "GLCHMK_001", "title": "G-LiHT Canopy Height Model KML V001", @@ -125657,6 +125657,19 @@ "description": "The Daily Moderate Resolution Imaging Spectroradiometer (MODIS) (Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) 30 arc second, Global Gap-Filled, Snow-Free, (MCD43GF) Version 6 is derived from the 30 arc second Climate Modeling Grid (CMG) MCD43D Version 6 product suite, with additional processing to provide a gap-filled, snow-free product. The highest quality full inversion values were used for the temporal fitting effort and supplemented with lower quality pixels, spatial fitting, and spatial smoothing as needed. The status of each pixel can be found in the quality layer for each band. To generate a snow-free product, pixels with ephemeral snow were removed using the MCD43D41 (https://doi.org/10.5067/MODIS/MCD43D41.006) snow flags. The underlying MCD43D utilizes a BRDF model derived from all available high quality cloud clear reflectance data over a 16 day moving window centered on and emphasizing the daily day of interest (the ninth day of each retrieval period as reflected in the Julian date in the filename). This 30arc second BRDF model is then used to produce the Albedo and NBAR products (MCD43D). These BRDF model parameters are computed for MODIS spectral bands 1 through 7 (0.47 um, 0.55 um, 0.67 um, 0.86 um, 1.24 um, 1.64 um, 2.1 um), as well as the shortwave infrared band (0.3-5.0um), visible band (0.3-0.7 um), and near-infrared (0.7-5.0 um) broad bands. The MCD43GF product includes 67 layers containing black-sky albedo (BSA) at local solar noon, isotropic (ISO), volumetric (VOL), geometric (GEO), quality (QA), Nadir BRDF-Adjusted Reflectance (NBAR) at local solar noon, and white-sky albedo (WSA). Due to the large file size, each data layer is distributed as a separate HDF file. Users are encouraged to download the quality layers for each of the 10 bands to check quality assessment information before using the BRDF/Albedo data. Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications (https://www.umb.edu/spectralmass/terra_aqua_modis/v006). The MCD43 product is not recommended for solar zenith angles beyond 70 degrees. The MODIS BRDF/Albedo products have achieved stage 3 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation. Improvements/Changes from Previous Versions Observations are weighted to estimate the BRDF/Albedo on the ninth day of the 16-day period. *\tMCD43 products use the snow status weighted to the ninth day instead of the majority snow/no-snow observations from the 16-day period. *\tBetter quality at high latitudes from use of all available observations for the acquisition period. Collection 5 used only four observations per day. *\tThe MCD43 products use L2G-lite surface reflectance as input. *\tIn cases where insufficient high-quality reflectances are obtained, a database with archetypal BRDF parameters is used to supplement the observational data and perform a lower quality magnitude inversion. This database is continually updated with the latest full inversion retrieval for each pixel. *\tCMG Albedo is estimated using all the clear-sky observations within the 1,000 m grid as opposed to aggregating from the 500 m albedo. Important Quality Information The incorrect representation of the aerosol quantities (low average high) in the C6 MYD09 and MOD09 surface reflectance products may have impacted down stream products particularly over arid bright surfaces (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/displayCase.cgi?esdt=MOD09&caseNum=PM_MOD09_20010&caseLocation=cases_data&type=C6). This (and a few other issues) have been corrected for C6.1. Therefore users should avoid substantive use of the C6 MCD43 products and wait for the C6.1 products. In any event, users are always strongly encouraged to download and use the extensive QA data provided in MCD43A2, in addition to the briefer mandatory QAs provided as part of the MCD43A1, 3, and 4 products. ", "license": "proprietary" }, + { + "id": "MCD43GF_061", + "title": "MODIS/Terra+Aqua BRDF/Albedo Gap-Filled Snow-Free Daily L3 Global 30ArcSec CMG V061", + "catalog": "LPCLOUD STAC Catalog", + "state_date": "2000-03-03", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3216719281-LPCLOUD.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3216719281-LPCLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections/MCD43GF_061", + "description": "The Daily Moderate Resolution Imaging Spectroradiometer (MODIS) (Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) 30 arc second, Global Gap-Filled, Snow-Free, (MCD43GF) Version 6.1 is derived from the 30 arc second Climate Modeling Grid (CMG) MCD43D Version 6.1 product suite, with additional processing to provide a gap-filled, snow-free product. The highest quality full inversion values were used for the temporal fitting effort and supplemented with lower quality pixels, spatial fitting, and spatial smoothing as needed. The status of each pixel can be found in the quality layer for each band. To generate a snow-free product, pixels with ephemeral snow were removed using the [MCD43D41](https://doi.org/10.5067/MODIS/MCD43D41.061) snow flags. The underlying MCD43D utilizes a BRDF model derived from all available high quality cloud clear reflectance data over a 16 day moving window centered on and emphasizing the daily day of interest (the ninth day of each retrieval period as reflected in the Julian date in the filename). This 30 arc second BRDF model is then used to produce the Albedo and NBAR products (MCD43D). These BRDF model parameters are computed for MODIS spectral bands 1 through 7 (0.47 um, 0.55 um, 0.67 um, 0.86 um, 1.24 um, 1.64 um, 2.1 um), as well as the shortwave infrared band (0.3-5.0 um), visible band (0.3-0.7 um), and near-infrared (0.7-5.0 um) broad bands. The MCD43GF product includes 67 layers containing black-sky albedo (BSA) at local solar noon, isotropic model parameter (ISO), volumetric model parameter (VOL), geometric model parameter (GEO), quality (QA), Nadir BRDF-Adjusted Reflectance (NBAR) at local solar noon, and white-sky albedo (WSA). Due to the large file size, each data layer is distributed as a separate HDF file. Users are encouraged to download the quality layers for each of the 10 bands to check quality assessment information before using the BRDF/Albedo data. The MCD43 product is not recommended for solar zenith angles beyond 70 degrees. Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the [User Guide](https://www.umb.edu/spectralmass/modis-user-guide-v006-and-v0061/mcd43gf-cmg-gap-filled-snow-free-products/). Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * In Version 6.1 reprocessing, the QA values for the MCD43GF product will change to reflect the band 5 and 6 dead detector issues. ", + "license": "proprietary" + }, { "id": "MCD64A1_061", "title": "MODIS/Terra+Aqua Direct Broadcast Burned Area Monthly L3 Global 500m SIN Grid V061", @@ -127443,7 +127456,7 @@ "title": "MiCASA 3-hourly NPP NEE Fluxes 0.1 degree x 0.1 degree", "catalog": "GES_DISC STAC Catalog", "state_date": "2001-01-01", - "end_date": "2023-12-31", + "end_date": "2024-07-31", "bbox": "-180, -90, 179, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3273640138-GES_DISC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3273640138-GES_DISC.html", @@ -127456,7 +127469,7 @@ "title": "MiCASA Daily NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree", "catalog": "GES_DISC STAC Catalog", "state_date": "2001-01-01", - "end_date": "2023-12-31", + "end_date": "2024-07-31", "bbox": "-180, -90, 179, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3273639213-GES_DISC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3273639213-GES_DISC.html", @@ -127469,7 +127482,7 @@ "title": "MiCASA Monthly NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree", "catalog": "GES_DISC STAC Catalog", "state_date": "2001-01-01", - "end_date": "2023-12-31", + "end_date": "2024-07-31", "bbox": "-180, -90, 179, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3273638632-GES_DISC.umm_json", "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3273638632-GES_DISC.html", @@ -152844,7 +152857,7 @@ "id": "PACE_EPH_DEF_1", "title": "PACE Definitive Ephemeris Data Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3020918309-OB_CLOUD.umm_json", @@ -152857,7 +152870,7 @@ "id": "PACE_HARP2_L0_1", "title": "PACE HARP2 Level-0 Instrument Telemetry/Multi-Detector Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.umm_json", @@ -152870,7 +152883,7 @@ "id": "PACE_HARP2_L0_D1_1", "title": "PACE HARP2 Level-0 Detector 1 (D1) Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.umm_json", @@ -152883,7 +152896,7 @@ "id": "PACE_HARP2_L0_D2_1", "title": "PACE HARP2 Level-0 Detector 2 (D2) Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.umm_json", @@ -152896,7 +152909,7 @@ "id": "PACE_HARP2_L0_D3_1", "title": "PACE HARP2 Level-0 Detector 3 (D3) Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.umm_json", @@ -152909,7 +152922,7 @@ "id": "PACE_HARP2_L0_REAL_1", "title": "PACE HARP2 Level-0 Real-time Direct Transfer Mode Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.umm_json", @@ -152922,7 +152935,7 @@ "id": "PACE_HARP2_L0_SCI_1", "title": "PACE HARP2 Level-0 Science Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.umm_json", @@ -153065,7 +153078,7 @@ "id": "PACE_HKT_1", "title": "PACE Spacecraft Housekeeping, NetCDF format Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2832273136-OB_CLOUD.umm_json", @@ -153078,7 +153091,7 @@ "id": "PACE_HSK_1", "title": "PACE Spacecraft Housekeeping Data, V1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2869693107-OB_CLOUD.umm_json", @@ -153091,7 +153104,7 @@ "id": "PACE_OCI_L0_DARK_1", "title": "PACE OCI Level-0 Dark Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798299-OB_CLOUD.umm_json", @@ -153104,7 +153117,7 @@ "id": "PACE_OCI_L0_DIAG_1", "title": "PACE OCI Level-0 Diagnostic/Calibaration Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798302-OB_CLOUD.umm_json", @@ -153117,7 +153130,7 @@ "id": "PACE_OCI_L0_LIN_1", "title": "PACE OCI Level-0 Linearity Calibration Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798304-OB_CLOUD.umm_json", @@ -153130,7 +153143,7 @@ "id": "PACE_OCI_L0_LUN_1", "title": "PACE OCI Level-0 Lunar Calibration Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798306-OB_CLOUD.umm_json", @@ -153143,7 +153156,7 @@ "id": "PACE_OCI_L0_RAW_1", "title": "PACE OCI Level-0 Raw Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798308-OB_CLOUD.umm_json", @@ -153156,7 +153169,7 @@ "id": "PACE_OCI_L0_SCI_1", "title": "PACE OCI Level-0 Science Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798309-OB_CLOUD.umm_json", @@ -153169,7 +153182,7 @@ "id": "PACE_OCI_L0_SNAPI_1", "title": "PACE OCI Level-0 Snapshot Internal Trigger Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798315-OB_CLOUD.umm_json", @@ -153182,7 +153195,7 @@ "id": "PACE_OCI_L0_SNAPX_1", "title": "PACE OCI Level-0 Snapshot External Trigger Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798322-OB_CLOUD.umm_json", @@ -153195,7 +153208,7 @@ "id": "PACE_OCI_L0_SOLD_1", "title": "PACE OCI Level-0 Daily Solar Calibration Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798329-OB_CLOUD.umm_json", @@ -153208,7 +153221,7 @@ "id": "PACE_OCI_L0_SOLM_1", "title": "PACE OCI Level-0 Monthly Solar Calibration Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798338-OB_CLOUD.umm_json", @@ -153221,7 +153234,7 @@ "id": "PACE_OCI_L0_SPEC_1", "title": "PACE OCI Level-0 Spectral Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798347-OB_CLOUD.umm_json", @@ -153234,7 +153247,7 @@ "id": "PACE_OCI_L0_STAT_1", "title": "PACE OCI Level-0 Static Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798354-OB_CLOUD.umm_json", @@ -154638,7 +154651,7 @@ "id": "PACE_SPEXONE_L0_1", "title": "PACE SPEXone Level-0 Data, version 1", "catalog": "OB_CLOUD STAC Catalog", - "state_date": "2024-02-25", + "state_date": "2024-02-08", "end_date": "", "bbox": "-180, -90, 180, 90", "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2816780240-OB_CLOUD.umm_json", @@ -178580,6 +178593,19 @@ "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the Pathfinder satellite, as the full version of the Level 1a geolocated antenna temperatures (radiance) in units of kelvins that are timestamped to UTC and are reported at native spatial resolutions. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.", "license": "proprietary" }, + { + "id": "TROPICS01TCIEL2B_1.0", + "title": "TROPICS01\u00a0Pathfinder\u00a0L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0", + "catalog": "GES_DISC STAC Catalog", + "state_date": "2021-07-19", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3280791029-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3280791029-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS01TCIEL2B_1.0", + "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023.", + "license": "proprietary" + }, { "id": "TROPICS01URADL2A_1.0", "title": "TROPICS01\u00a0Pathfinder\u00a0L2A Unified Resolution Brightness Temperatures V1.0", @@ -178645,6 +178671,19 @@ "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles.\u00a0See README for this and other calibration observations and the Data Product Users Guide for orbit details.", "license": "proprietary" }, + { + "id": "TROPICS03TCIEL2B_1.0", + "title": "TROPICS03\u00a0L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0", + "catalog": "GES_DISC STAC Catalog", + "state_date": "2021-07-19", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3279630448-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3279630448-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS03TCIEL2B_1.0", + "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023.", + "license": "proprietary" + }, { "id": "TROPICS03URADL2A_1.0", "title": "TROPICS03\u00a0L2A Unified Resolution Brightness Temperatures V1.0", @@ -178762,6 +178801,19 @@ "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles.\u00a0See README for this and other calibration observations and the Data Product Users Guide for orbit details.", "license": "proprietary" }, + { + "id": "TROPICS06TCIEL2B_1.0", + "title": "TROPICS06\u00a0L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0", + "catalog": "GES_DISC STAC Catalog", + "state_date": "2021-07-19", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3280808959-GES_DISC.umm_json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3280808959-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/TROPICS06TCIEL2B_1.0", + "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023.", + "license": "proprietary" + }, { "id": "TROPICS06URADL2A_1.0", "title": "TROPICS06\u00a0L2A Unified Resolution Brightness Temperatures V1.0", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index dbeea37..69e8624 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -2423,40 +2423,40 @@ AST_L1T_031 ASTER Level 1 Precision Terrain Corrected Registered At-Sensor Radia ATCS_0 The A-Train Cloud Segmentation Dataset OB_DAAC STAC Catalog 2007-11-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2172083412-OB_DAAC.umm_json ATCS is a dataset designed to train deep learning models to volumetrically segment clouds from multi-angle satellite imagery. The dataset consists of spatiotemporally aligned patches of multi-angle polarimetry from the POLDER sensor aboard the PARASOL mission and vertical cloud profiles from the 2B-CLDCLASS product using the cloud profiling radar (CPR) aboard CloudSat. proprietary ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. proprietary ATL02_006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. proprietary -ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary +ATL03_006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. proprietary ATL03_ANC_MASKS_1 ATLAS/ICESat-2 ATL03 Ancillary Masks, Version 1 NSIDCV0 STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2278879612-NSIDCV0.umm_json This ancillary ICESat-2 data set contains four static surface masks (land ice, sea ice, land, and ocean) provided by ATL03 to reduce the volume of data that each surface-specific along-track data product is required to process. For example, the land ice surface mask directs the ATL06 land ice algorithm to consider data from only those areas of interest to the land ice community. Similarly, the sea ice, land, and ocean masks direct ATL07, ATL08, and ATL12 algorithms, respectively. A detailed description of all four masks can be found in section 4 of the Algorithm Theoretical Basis Document (ATBD) for ATL03 linked under technical references. proprietary -ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL04_006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL06_006 ATLAS/ICESat-2 L3A Land Ice Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL07QL_006 ATLAS/ICESat-2 L3A Sea Ice Height Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548344839-NSIDC_ECS.umm_json ATL07QL is the quick look version of ATL07. Once final ATL07 files are available, the corresponding ATL07QL files will be removed. ATL07 contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary -ATL07_006 ATLAS/ICESat-2 L3A Sea Ice Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.umm_json The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL07_006 ATLAS/ICESat-2 L3A Sea Ice Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.umm_json The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL07_006 ATLAS/ICESat-2 L3A Sea Ice Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.umm_json The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL08QL_006 ATLAS/ICESat-2 L3A Land and Vegetation Height Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548345108-NSIDC_ECS.umm_json ATL08QL is the quick look version of ATL08. Once final ATL08 files are available the corresponding ATL08QL files will be removed. ATL08 contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary -ATL08_006 ATLAS/ICESat-2 L3A Land and Vegetation Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.umm_json This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL08_006 ATLAS/ICESat-2 L3A Land and Vegetation Height V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.umm_json This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL08_006 ATLAS/ICESat-2 L3A Land and Vegetation Height V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.umm_json This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL09QL_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2551528419-NSIDC_ECS.umm_json ATL09QL is the quick look version of ATL09. Once final ATL09 files are available the corresponding ATL09QL files will be removed. ATL09 contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary -ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.umm_json This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL09_006 ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10QL_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2551529078-NSIDC_ECS.umm_json ATL10QL is the quick look version of ATL10. Once final ATL10 files are available the corresponding ATL10QL files will be removed. ATL10 contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL10_006 ATLAS/ICESat-2 L3A Sea Ice Freeboard V006 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2752556504-NSIDC_CPRD.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary ATL11_006 ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2750966856-NSIDC_ECS.umm_json This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations. proprietary -ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary +ATL12_006 ATLAS/ICESat-2 L3A Ocean Surface Height V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. proprietary ATL13QL_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data Quick Look V006 NSIDC_ECS STAC Catalog 2024-08-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650092501-NSIDC_ECS.umm_json ATL13QL is the quick look version of ATL13. Once final ATL13 files are available the corresponding ATL13QL files will be removed. ATL13 contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7 km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary ATL13_006 ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2650116584-NSIDC_ECS.umm_json This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit). proprietary -ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary -ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL14_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_ECS STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary -ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary +ATL14_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_ECS STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary -ATL15_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004 NSIDC_ECS STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159684532-NSIDC_ECS.umm_json This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL15_003 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003 NSIDC_CPRD STAC Catalog 2019-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change. proprietary ATL15_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004 NSIDC_CPRD STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary +ATL15_004 ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004 NSIDC_ECS STAC Catalog 2019-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3159684532-NSIDC_ECS.umm_json This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11). proprietary ATL16_005 ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2769337070-NSIDC_CPRD.umm_json This product reports weekly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary ATL16_005 ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737997243-NSIDC_ECS.umm_json This product reports weekly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary ATL17_005 ATLAS/ICESat-2 L3B Monthly Gridded Atmosphere V005 NSIDC_ECS STAC Catalog 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737997483-NSIDC_ECS.umm_json This data set contains a gridded summary of monthly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency. proprietary @@ -2467,10 +2467,10 @@ ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NS ATL20_004 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2666857908-NSIDC_ECS.umm_json ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection. proprietary ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary ATL21_003 ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids. proprietary -ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_CPRD STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary -ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary +ATL22_003 ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003 NSIDC_ECS STAC Catalog 2018-10-14 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers. proprietary ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_CPRD STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary +ATL23_001 ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001 NSIDC_ECS STAC Catalog 2018-10-13 -180, -88, 180, 88 https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates. proprietary ATLAS_DEALIASED_SASS_L2_1 SEASAT SCATTEROMETER DEALIASED OCEAN WIND VECTORS (Atlas) POCLOUD STAC Catalog 1978-07-07 1978-10-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2617197627-POCLOUD.umm_json Contains wind speeds and directions derived from the Seasat-A Scatterometer (SASS), presented chronologically by swath for the period between 7 July 1978 and 10 October 1978. Robert Atlas et al. (1987) produced this product using an objective ambiguity removal scheme to dealias the wind vector data binned at 100 km cells, which were calculated by Frank Wentz. proprietary ATLAS_Veg_Plots_1541_1 Arctic Vegetation Plots ATLAS Project North Slope and Seward Peninsula, AK, 1998-2000 ORNL_CLOUD STAC Catalog 1998-07-01 2000-07-29 -165.07, 64.73, -153.74, 71.32 https://cmr.earthdata.nasa.gov/search/concepts/C2162120307-ORNL_CLOUD.umm_json This data set provides environmental, soil, and vegetation data collected from study sites on the North Slope and Seward Peninsula of Alaska during the Arctic Transition in Land-Atmosphere System (ATLAS) project. ATLAS-1 sites on the North Slope, located in Barrow, Atqasuk, Oumalik, and Ivotuk, were sampled in 1998-1999. ATLAS-2 sites located at Council and Quartz Creek on the Seward Peninsula were sampled in 2000. Specific attributes include dominant vegetation species and cover, biomass, soil chemistry and moisture, leaf area index (LAI), normalized difference vegetation index (NDVI), topography and elevation, and plant cover abundance. proprietary ATMOSL1_3 ATMOS L1 Spectra and Runlogs V3 (ATMOSL1) at GES DISC GES_DISC STAC Catalog 1985-04-30 1994-11-12 -180, -73, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2234896943-GES_DISC.umm_json This is the version 3 Atmospheric Trace Molecule Spectroscopy (ATMOS) Level 1 product containing spectra and runlog (i.e. ) information in a netCDF format. ATMOS is an infrared spectrometer (a Fourier transform interferometer) designed to derive vertical concentrations of various trace gases in the atmosphere, particularly the ozone depleting chlorine and fluorine based molecules. The transmission spectra are ratioed from ATMOS high sun observations, on a scale of 0 to 1. Data files also include time, geolocation and other information. The data were collected during four space shuttle missions: STS-51B/Spacelab 3 (April 30 to May 1, 1985), STS-45/ATLAS-1 (March 25 to April 2, 1992), STS-55/ATLAS-2 (April 8 to 16, 1993), and STS-66/ATLAS-3 (November 3 to 12, 1994). Data are written to separate files grouped by mission (sl3, at1, at2 or at3), and occultation type (sunrise or sunset) and number. proprietary @@ -3719,7 +3719,7 @@ CER_BDS_Terra-FM1_Edition4 CERES BDS Terra FM1 Edition 4 LARC_ASDC STAC Catalog CER_BDS_Terra-FM2_Edition1-CV CERES Bidirectional Scans Terra FM2 Edition1-CV LARC_ASDC STAC Catalog 2000-02-25 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C4254869-LARC_ASDC.umm_json CER_BDS_Terra-FM2_Edition1-CV is the Clouds and the Earth's Radiant Energy System (CERES) Bidirectional Scans (BDS) Terra Flight Model 2 (FM2) Edition1-CV data product, which was collected using the CERES-FM2 instrument on the Terra platform. This data product is intended only to be used for instrument validation purposes and is, therefore, not suited for science publications. Data collection for this product is ongoing. Note: Edition 1-CV data are only for instrument validation and not suited for science publications. Each CERES BDS data product contains twenty-four hours of Level-1B data for each CERES scanner instrument mounted on each spacecraft. BDS includes samples of normal and short Earth scan elevation profiles in fixed and rotating azimuth modes (including space, internal calibration, and solar calibration views). BDS contains Level-0 raw (unconverted) and the geolocated converted science and instrument data. BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. CERES is a key Earth Observing System (EOS) program component. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the proto flight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017. proprietary CER_BDS_Terra-FM2_Edition4 CER_BDS_Terra-FM2_Edition4 LARC_ASDC STAC Catalog 2000-03-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C7460995-LARC_ASDC.umm_json CER_BDS_Terra-FM2_Edition4 is the Clouds and the Earth's Radiant Energy System (CERES) Bidirectional Scans (BDS) Terra Flight Model 2 (FM2) Edition 4 data product, which is collected using the CERES-FM2 instrument on the Terra platform. CER_BDS_Terra-FM2_Edition4 includes geolocated and calibrated Top of the Atmosphere (TOA) filtered radiances and other instrument data. Data collection for this product is ongoing. Each CERES BDS data product contains twenty-four hours of Level-1B data for each CERES scanner instrument mounted on each spacecraft. BDS includes samples of normal and short Earth scan elevation profiles in fixed and rotating azimuth modes (including space, internal calibration, and solar calibration views). BDS contains Level-0 raw (unconverted) and the geolocated converted science and instrument data. BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. CERES is a key Earth Observing System (EOS) program component. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the proto flight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit onboard the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched onboard the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched onboard the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017. proprietary CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD1 CERES A-Train Integrated CALIPSO, CloudSat, CERES, and MODIS (CCCM) Merged Release D1 LARC_ASDC STAC Catalog 2006-07-01 2011-04-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2146741027-LARC_ASDC.umm_json CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD1 is the Clouds and the Earth's Radiant Energy System (CERES) A-Train Integrated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), CloudSat Cloudsat, CERES, and Moderate-Resolution Imaging Spectroradiometer (MODIS) (CCCM) Merged Release D1 data product. Data was collected using the CALIOP on CALIPSO, Cloudsat Cloud Profiling Radar (CPR), CERES Flight Model 3 (FM3), CERES Scanner, and MODIS on Aqua. The CALIPSO-CloudSat-CERES-MODIS (CCCM) data set integrates measurements from the CALIPSO CALIOP instrument, CloudSat Cloud Profiling Radar (CPR), CERES, and the MODIS data. The cloud and aerosol properties from CALIOP and cloud properties from the CPR are matched to a MODIS pixel and then an Aqua CERES footprint. The product contains only the CERES footprint in each scan with the highest CALIPSO and CloudSat ground track coverage. The product consists of all cloud and aerosol properties derived from MODIS radiances included in the Single Scanner Footprint (SSF) product and computed irradiances included in the Cloud Radiative Swath (CRS) product. Two sets of SSF variables are included in the CCCM data. One set covers the entire CERES footprint, and the other set is only over the CALIOP and CPR ground track. CERES-derived top-of-atmosphere (TOA) shortwave (SW), longwave (LW), and window (WN) irradiances by angular distribution models are also included. In addition, irradiance profiles computed by a radiative transfer model using MODIS, CALIOP, and CPR-derived aerosol, clouds, and surface properties are included in the product. Furthermore, MODIS-derived cloud properties from the algorithm incorporating CALIOP instrument data and CPR cloud information are also included. MODIS-derived cloud properties and TOA irradiances derived from CERES radiances are produced by the same algorithm that produces CERES SSF and CRS products. However, the CCCM product should not be considered a climate data record since various input data product versions and algorithm modifications will occur during the measurement period. The scan and packet numbers unique to the CERES footprint provide the means to match the data to other CERES products, although the CCCM product contains more near-nadir CERES footprints compared with SSF and CRS products. The resulting HDF granule contains 24 hours of data.CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the Proto-Flight Model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments, Flight Models 1 and 2 (FM1 and FM2), were launched into polar orbit onboard the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments, Flight Models 3 and 4 (FM3 and FM4), were launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. The CERES Flight Model 5 (FM5) instrument was launched onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite on October 28, 2011. The newest CERES instrument, Flight Model 6 (FM6), was launched onboard the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017. RelD1 incorporates the latest CERES SSF algorithms and CALIPSO and CloudSat data versions. An additional input is the CloudSat 2C-ICE product. This version also includes single short CALIPSO cloud information. proprietary -CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD2 CERES A-Train Integrated CALIPSO, CloudSat, CERES, and MODIS (CCCM) Merged Release D2 LARC_ASDC STAC Catalog 2006-07-01 2011-04-30 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3091018780-LARC_ASDC.umm_json CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD2 is Release D2 of a highly fused Level 2 data product that uses multiple satellites and instruments in the Afternoon Train or A-Train to produce high-resolution vertical computed atmosphere fluxes. From Aqua, the Clouds and the Earth's Radiant Energy System (CERES) Flight Model 3 (FM3) and Moderate-Resolution Imaging Spectroradiometer (MODIS); from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP); and from CloudSat, the Cloud Profiling Radar (CPR) instruments are used in the product. The CCCM product name indicates the CALIPSO, CloudSat, CERES, and MODIS merged data synergy. The cloud and aerosol properties from CALIOP and cloud properties from the CPR are used to create high-resolution vertical profiles and sixteen horizontal groupings of cloud and aerosol that are then matched to a MODIS pixel and then convolved into Aqua CERES footprints. The product contains only the CERES footprint in each scan, which has the highest CALIPSO and CloudSat ground track coverage. The high-resolution information is used to compute within-atmosphere irradiance profiles using the Fu-Liou radiation transfer model (RTM). Four assumptions are used in the RTM: Total-sky, clear-sky (no clouds, but aerosol), pristine (no clouds or aerosols), and total-sky, no aerosol. The product also contains variables from the Single Scanner Footprint (SSF) product, including CERES-derived top-of-atmosphere (TOA) shortwave (SW), longwave (LW), and window (WN) irradiances obtained using angular distribution models and computed irradiances included in the Cloud Radiative Swath (CRS) product based on cloud and aerosol properties derived only from MODIS radiances. Two sets of SSF variables are included in the CCCM data. One set uses imager data covering the entire CERES footprint, and the other set only uses imager pixel data that matches with the CALIOP and CPR ground track. However, the CCCM product should not be considered a climate data record since various input data product versions and algorithm modifications will occur during the measurement period. The scan and packet numbers unique to the CERES footprint provide the means to match the data to other CERES products, although the CCCM product contains more near-nadir CERES footprints that are not in the standard SSF, CER_SSF_Aqua-FM3-MODIS_Edition4A, and CRS, CER_CRS_Aqua-FM3-MODIS_Edition2C, products. The resulting daily HDF granule contains 24 hours of data along the satellite track covering the globe. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The CERES instrument, Flight Models 3 (FM3), was launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. CloudSat was selected as a NASA Earth System Science Pathfinder satellite mission in 1999 to provide observations necessary to advance our understanding of cloud abundance, distribution, structure, and radiative properties. It also launched on April 28, 2006. proprietary +CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD2 CERES A-Train Integrated CALIPSO, CloudSat, CERES, and MODIS (CCCM) Merged Release D2 LARC_ASDC STAC Catalog 2006-07-01 2017-12-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3091018780-LARC_ASDC.umm_json CER_CCCM_Aqua-FM3-MODIS-CAL-CS_RelD2 is Release D2 of a highly fused Level 2 data product that uses multiple satellites and instruments in the Afternoon Train or A-Train to produce high-resolution vertical computed atmosphere fluxes. From Aqua, the Clouds and the Earth's Radiant Energy System (CERES) Flight Model 3 (FM3) and Moderate-Resolution Imaging Spectroradiometer (MODIS); from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP); and from CloudSat, the Cloud Profiling Radar (CPR) instruments are used in the product. The CCCM product name indicates the CALIPSO, CloudSat, CERES, and MODIS merged data synergy. The cloud and aerosol properties from CALIOP and cloud properties from the CPR are used to create high-resolution vertical profiles and sixteen horizontal groupings of cloud and aerosol that are then matched to a MODIS pixel and then convolved into Aqua CERES footprints. The product contains only the CERES footprint in each scan, which has the highest CALIPSO and CloudSat ground track coverage. The high-resolution information is used to compute within-atmosphere irradiance profiles using the Fu-Liou radiation transfer model (RTM). Four assumptions are used in the RTM: Total-sky, clear-sky (no clouds, but aerosol), pristine (no clouds or aerosols), and total-sky, no aerosol. The product also contains variables from the Single Scanner Footprint (SSF) product, including CERES-derived top-of-atmosphere (TOA) shortwave (SW), longwave (LW), and window (WN) irradiances obtained using angular distribution models and computed irradiances included in the Cloud Radiative Swath (CRS) product based on cloud and aerosol properties derived only from MODIS radiances. Two sets of SSF variables are included in the CCCM data. One set uses imager data covering the entire CERES footprint, and the other set only uses imager pixel data that matches with the CALIOP and CPR ground track. However, the CCCM product should not be considered a climate data record since various input data product versions and algorithm modifications will occur during the measurement period. The scan and packet numbers unique to the CERES footprint provide the means to match the data to other CERES products, although the CCCM product contains more near-nadir CERES footprints that are not in the standard SSF, CER_SSF_Aqua-FM3-MODIS_Edition4A, and CRS, CER_CRS_Aqua-FM3-MODIS_Edition2C, products. The resulting daily HDF granule contains 24 hours of data along the satellite track covering the globe. CERES is a key component of the Earth Observing System (EOS) program. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The CERES instrument, Flight Models 3 (FM3), was launched onboard Earth Observing System (EOS) Aqua on May 4, 2002. CALIPSO is a joint satellite mission between NASA and the French Agency CNES (Centre National d'Etudes Spatiales). CALIPSO was launched on April 28, 2006, to study the impact of clouds and aerosols on the Earth's radiation budget and climate. CloudSat was selected as a NASA Earth System Science Pathfinder satellite mission in 1999 to provide observations necessary to advance our understanding of cloud abundance, distribution, structure, and radiative properties. It also launched on April 28, 2006. proprietary CER_CRS1deg-Hour_Aqua-MODIS_Edition4A CERES Regionally Averaged Computed TOA, within the Atmosphere, and Surface Fluxes Hourly Aqua Edition4A LARC_ASDC STAC Catalog 2018-01-01 2022-12-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2842856368-LARC_ASDC.umm_json CER_CRS1deg-Hour_Aqua-MODIS_Edition4A is the Aqua Clouds and the Earth's Radiant Energy System (CERES) Level 3 computed flux Edition4A data product. The Cloud and Radiative Swath One Degree (CRS1deg) Hour provides data hourly on a 1-degree latitude and longitude global grid from the Aqua CERES Flight Model 3 (FM3) or FM4 CER_CRS_Aqua-FM3-MODIS_Edition4A instantaneous footprint data. The data provides instantaneous averages of computed top of atmosphere (ToA) (0.01-hPa), within the atmosphere (850-, 500-, 200-, and 70-hPa), and surface fluxes (Wm-2). Four assumptions are used in the Fu-Liou radiative transfer model (RTM): Total-sky, clear-sky (no clouds, but aerosol), pristine (no clouds or aerosols), and total-sky, no aerosol as described in Scott 2022. Variables from these footprints are then assigned to a grid box and linearly averaged. The data has been processed from January 1, 2018, to December 31, 2022, and is available in daily netCDF4 files. This single satellite product uses the primary CERES instrument in cross-track mode. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels: total, shortwave, and window. Longwave fluxes are obtained by subtracting shortwave from the total. A few variables from the SSF have been included in this product, such as observed CERES shortwave and longwave ToA fluxes and cloud fraction. MODIS measurements are not directly used in this dataset. The MODIS data is used during SSF processing to obtain cloud properties. These cloud properties are then used to compute the CRS fluxes. Still, this product should be used in conjunction with the CER_SSF1deg-Hour_Aqua-MODIS_Edition4A product, which has additional cloud and aerosol properties. The CER_SYN1deg-1Hour_Terra-Aqua-MODIS_Edition4A is another related product that averages the cloud properties to the one-degree grid before performing the Fu-Liou RTM calculations. The SYN1deg-1Hour product also brings in cloud properties derived from geostationary imagers between 60 N and 60 S to provide information to provide a complete diurnal cycle. proprietary CER_CRS1deg-Hour_Terra-MODIS_Edition4A CERES Regionally Averaged Computed TOA, within the Atmosphere, and Surface Fluxes Hourly Terra Edition4A LARC_ASDC STAC Catalog 2018-01-01 2022-12-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2842857656-LARC_ASDC.umm_json CER_CRS1deg-Hour_Terra-MODIS_Edition4A is the Terra Clouds and the Earth's Radiant Energy System (CERES) Level 3 computed flux Edition4A data product. The Cloud and Radiative Swath One Degree (CRS1deg) Hour provides data hourly on a 1-degree latitude and longitude global grid from the Terra CERES Flight Model 1 (FM1) or FM2 CER_CRS_Terra-FM1-MODIS_Edition4A instantaneous footprint data. The data provides instantaneous averages of computed top of atmosphere (ToA) (0.01-hPa), within the atmosphere (850-, 500-, 200-, and 70-hPa), and surface fluxes (Wm-2). Four assumptions are used in the Fu-Liou radiative transfer model (RTM): Total-sky, clear-sky (no clouds, but aerosol), pristine (no clouds or aerosols), and total-sky, no aerosol as described in Scott 2022. Variables from these footprints are then assigned to a grid box and linearly averaged. The data has been processed from January 1, 2018, to December 31, 2022, and is available in daily netCDF4 files. This single satellite product uses the primary CERES instrument in cross-track mode. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels: total, shortwave, and window. Longwave fluxes are obtained by subtracting shortwave from the total. A few variables from the SSF have been included in this product, such as observed CERES shortwave and longwave ToA fluxes and cloud fraction. MODIS measurements are not directly used in this dataset. The MODIS data is used during SSF processing to obtain cloud properties. These cloud properties are then used to compute the CRS fluxes. Still, this product should be used in conjunction with the CER_SSF1deg-Hour_Terra-MODIS_Edition4A product, which has additional cloud and aerosol properties. The CER_SYN1deg-1Hour_Terra-Aqua-MODIS_Edition4A is another related product that averages the cloud properties to the one-degree grid before performing the Fu-Liou RTM calculations. The SYN1deg-1Hour product also brings in cloud properties derived from geostationary imagers between 60 N and 60 S to provide information to provide a complete diurnal cycle. proprietary CER_CRS_Aqua-FM3-MODIS_Edition2B CERES Clouds and Radiative Swath (CRS) Aqua-FM3 MODIS Edition2B LARC_ASDC STAC Catalog 2002-07-02 2006-05-01 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C4331612-LARC_ASDC.umm_json "CER_CRS_Aqua-FM3-MODIS_Edition2B is the Clouds and the Earth's Radiant Energy System (CERES) Clouds and Radiative Swath (CRS) Aqua-Flight Model 3 (FM3) Moderate-Resolution Imaging Spectroradiometer (MODIS) Edition2B data product, which was collected using the CERES-FM3 instrument on the Aqua platform. Data collection for this product is complete. Note that more recent (2006) CRS Ed2C fields for untuned SW (upper left for all-sky globe and lower right for clear-sky ocean) show a bit more bias than does an average of the earlier (2002-2005) Clouds and Radiative Swath (CRS) Ed2B. CRS Ed2C (Ed2B) biases are evaluated for SSF Ed2C (Ed2B) observations, and those Single Scanner Footprint (SSF) observations do not include recent ""Rev1"" adjustments to observations. The CRS product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF, the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model, and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017." proprietary @@ -3937,9 +3937,9 @@ CIESIN_SEDAC_AQDH_DAO3_US_1KM_1.10_1.10 Daily 8-Hour Maximum and Annual O3 Conce CIESIN_SEDAC_AQDH_DAPM25_US_1KM_1.0 Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) SEDAC STAC Catalog 2000-01-01 2016-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2091764506-SEDAC.umm_json The Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) data set includes predictions of PM2.5 concentrations in grid cells at a resolution of 1 km for the years 2000 to 2016. A generalized additive model was used that accounted for geographic difference to ensemble daily predictions of three machine learning models: neural network, random forest, and gradient boosting. The three machine learners incorporated multiple predictors, including satellite data, meteorological variables, land-use variables, elevation, chemical transport model predictions, several reanalysis data sets, as well as other predictors. The annual predictions were calculated by averaging the daily predictions for each year in each grid cell. The ensembled model demonstrated better predictive performance than the individual machine learners with 10-fold cross-validated R-squared values of 0.86 for daily predictions and 0.89 for annual predictions. proprietary CIESIN_SEDAC_AQDH_DAPM25_US_1KM_1.10_1.10 Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, Version 1.10 (2000-2016) SEDAC STAC Catalog 2000-01-01 2016-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2848642054-SEDAC.umm_json The Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, Version 1.10 (2000-2016) data set includes predictions of PM2.5 concentration in grid cells at a resolution of 1-km for the years 2000-2016. A generalized additive model was used that accounted for geographic difference to ensemble daily predictions of three machine learning models: neural network, random forest, and gradient boosting. The three machine learners incorporated multiple predictors, including satellite data, meteorological variables, land-use variables, elevation, chemical transport model predictions, several reanalysis data sets, and others. The annual predictions were calculated by averaging the daily predictions for each year in each grid cell. The ensembled model demonstrated better predictive performance than the individual machine learners with 10-fold cross-validated R-squared values of 0.86 for daily predictions and 0.89 for annual predictions. In version 1.10, the completeness of daily PM2.5 predictions have been enhanced by employing linear interpolation to impute missing values. Specifically, for days with small spatial patches of missing data with less than 100 grid cells, inverse distance weighting interpolation was used to fill the missing grid cells. Other missing daily PM2.5 predictions were interpolated from the nearest days with available data. Annual predictions were updated by averaging the imputed daily predictions for each year in each grid cell. These daily and annual PM2.5 predictions allow public health researchers to respectively estimate the short- and long-term effects of PM2.5 exposures on human health, supporting the U.S. Environmental Protection Agency (EPA) for the revision of the National Ambient Air Quality Standards for 24-hour average and annual average concentrations of PM2.5. The data are available in RDS and GeoTIFF formats for statistical research and geospatial analysis. proprietary CIESIN_SEDAC_AQDH_NO2_US_1KM_1.00 Daily and Annual NO2 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) SEDAC STAC Catalog 2000-01-01 2016-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2302636732-SEDAC.umm_json The Daily and Annual NO2 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000-2016) data set contains daily predictions of Nitrogen Dioxide (NO2) concentrations at a high resolution (1 km x 1 km grid cells) for the years 2000 to 2016. An ensemble modeling framework was used to assess NO2 levels with high accuracy, which combined estimates from three machine learning models (neural network, random forest, and gradient boosting), with a generalized additive model. Predictor variables included NO2 column concentrations from satellites, land-use variables, meteorological variables, predictions from two chemical transport models, GEOS-Chem and the U.S. Environmental Protection Agency (EPA) CommUnity Multiscale Air Quality Modeling System (CMAQ), along with other ancillary variables. The annual predictions were calculated by averaging the daily predictions for each year in each grid cell. The ensemble produced a cross-validated R-squared value of 0.79 overall, a spatial R-squared value of 0.84, and a temporal R-squared value of 0.73. proprietary -CIESIN_SEDAC_AQDH_PM25COM_US_1KM_1.00 Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019 v1 SEDAC STAC Catalog 2000-01-01 2019-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2673736502-SEDAC.umm_json The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 �m (PM2.5) increases mortality and morbidity. PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019. Using Machine-Learning models (ML), combined with either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA) or Super-Learning (SL) and approximately 82 billion predictions across 20 years, hyperlocal super-learned PM2.5 components are now available for further research. The overall R-squared values of 10-fold cross validated models ranged from 0.910 to 0.970 on the training sets for these components, while on the test sets the R-squared values ranged from 0.860 to 0.960. Remarkable spatiotemporal intra-urban and inter-urban variabilities were found in PM2.5 components. The Coordinate Reference System (CRS) for predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components are �g/m^3. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python. proprietary +CIESIN_SEDAC_AQDH_PM25COM_US_1KM_1.00 Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019 v1 SEDAC STAC Catalog 2000-01-01 2019-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2673736502-SEDAC.umm_json The Annual Mean PM2.5 Components (EC, NH4, NO3, OC, SO4) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of the chemical concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and at a high resolution (1km x 1km grid cells) in non-urban areas for the years 2000 to 2019. Particulate matter with an aerodynamic diameter less than 2.5 microgram per cubic meter (PM2.5) increases mortality and morbidity. PM2.5 is composed of a mixture of chemical components that vary across space and time. Due to limited hyperlocal data availability, less is known about health risks of PM2.5 components, their U.S.-wide exposure disparities, or which species are driving the biggest intra-urban changes in PM2.5 mass. The national super-learned models were developed across the U.S. for hyperlocal estimation of annual mean elemental carbon, ammonium, nitrate, organic carbon, and sulfate concentrations across 3,535 urban areas at a 50m spatial resolution, and at a 1km resolution for non-urban areas from 2000 to 2019. Using Machine-Learning models (ML), combined with either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA) or Super-Learning (SL) and approximately 82 billion predictions across 20 years, hyperlocal super-learned PM2.5 components are now available for further research. The overall R-squared values of 10-fold cross validated models ranged from 0.910 to 0.970 on the training sets for these components, while on the test sets the R-squared values ranged from 0.860 to 0.960. Remarkable spatiotemporal intra-urban and inter-urban variabilities were found in PM2.5 components. The Coordinate Reference System (CRS) for predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components are microgram per cubic meter. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python. proprietary CIESIN_SEDAC_AQDH_PM25O3NO2_ZIPCODE_1.00 Daily and Annual PM2.5, O3, and NO2 Concentrations at ZIP Codes for the Contiguous U.S., 2000-2016, v1.0 SEDAC STAC Catalog 2000-01-01 2016-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2563727886-SEDAC.umm_json The Daily and Annual PM2.5, O3, and NO2 Concentrations at ZIP Codes for the Contiguous U.S., 2000-2016, v1.0 data set contains daily and annual concentration predictions for Fine Particulate Matter (PM2.5), Ozone (O3), and Nitrogen Dioxide (NO2) pollutants at ZIP Code-level for the years 2000 to 2016. Ensemble predictions of three machine-learning models were implemented (Random Forest, Gradient Boosting, and Neural Network) to estimate the daily PM2.5, O3, and NO2 at the centroids of 1km x 1km grid cells across the contiguous U.S. for 2000 to 2016. The predictors included air monitoring data, satellite aerosol optical depth, meteorological conditions, chemical transport model simulations, and land-use variables. The ensemble models demonstrated excellent predictive performance with 10-fold cross-validated R-squared values of 0.86 for PM2.5, 0.86 for O3, and 0.79 for NO2. These high-resolution, well-validated predictions allow for estimates of ZIP Code-level pollution concentrations with a high degree of accuracy. For general ZIP Codes with polygon representations, pollution levels were estimated by averaging the predictions of grid cells whose centroids lie inside the polygon of that ZIP Code; for other ZIP Codes such as Post Offices or large volume single customers, they were treated as a single point and predicted their pollution levels by assigning the predictions using the nearest grid cell. The polygon shapes and points with latitudes and longitudes for ZIP Codes were obtained from Esri and the U.S. ZIP Code Database and were updated annually. The data include about 31,000 general ZIP Codes with polygon representations, and about 10,000 ZIP Codes as single points. The aggregated ZIP Code-level, daily predictions are applicable in research such as environmental epidemiology, environmental justice, health equity, and political science, by linking with ZIP Code-level demographic and medical data sets, including national inpatient care records, medical claims data, census data, U.S. Census Bureau American CommUnity Survey (ACS), and Area Deprivation Index (ADI). The data are particularly useful for studies on rural populations who are under-represented due to the lack of air monitoring sites in rural areas. Compared with the 1km grid data, the ZIP Code-level predictions are much smaller in size and are manageable in personal computing environments. This greatly improves the inclusion of scientists in different fields by lowering the key barrier to participation in air pollution research. The Units are ug/m^3 for PM2.5 and ppb for O3 and NO2. proprietary -CIESIN_SEDAC_AQDH_TRACE_US_1KM_1.00 Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 SEDAC STAC Catalog 2000-01-01 2019-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2673738199-SEDAC.umm_json The Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of trace elements concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and a high resolution (1km x 1km grid cells) in non-urban areas, for the years 2000 to 2019. Particulate matter with an aerodynamic diameter of less than 2.5 �m (PM2.5) is a human silent killer of millions worldwide, and contains many trace elements (TEs). Understanding the relative toxicity is largely limited by the lack of data. In this work, ensembles of machine learning models were used to generate approximately 163 billion predictions estimating annual mean PM2.5 TEs, namely Bromine (Br), Calcium (Ca), Copper (Cu), Iron (Fe), Potassium (K), Nickel (Ni), Lead (Pb), Silicon (Si), Vanadium (V), and Zinc (Zn). The monitored data from approximately 600 locations were integrated with more than 160 predictors, such as time and location, satellite observations, composite predictors, meteorological covariates, and many novel land use variables using several machine learning algorithms and ensemble methods. Multiple machine-learning models were developed covering urban areas and non-urban areas. Their predictions were then ensembled using either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA), or Super-Learners. The overall best model R-squared values for the test sets ranged from 0.79 for Copper to 0.88 for Zinc in non-urban areas. In urban areas, the R-squared model values ranged from 0.80 for Copper to 0.88 for Zinc. The Coordinate Reference System (CRS) used in the predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components TEs are ng/m^3. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python. proprietary +CIESIN_SEDAC_AQDH_TRACE_US_1KM_1.00 Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 SEDAC STAC Catalog 2000-01-01 2019-12-31 -180, 17, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2673738199-SEDAC.umm_json The Annual Mean PM2.5 Components Trace Elements (TEs) 50m Urban and 1km Non-Urban Area Grids for Contiguous U.S., 2000-2019, v1 data set contains annual predictions of trace elements concentrations at a hyper resolution (50m x 50m grid cells) in urban areas and a high resolution (1km x 1km grid cells) in non-urban areas, for the years 2000 to 2019. Particulate matter with an aerodynamic diameter of less than 2.5 microgram per cubic meter (PM2.5) is a human silent killer of millions worldwide, and contains many trace elements (TEs). Understanding the relative toxicity is largely limited by the lack of data. In this work, ensembles of machine learning models were used to generate approximately 163 billion predictions estimating annual mean PM2.5 TEs, namely Bromine (Br), Calcium (Ca), Copper (Cu), Iron (Fe), Potassium (K), Nickel (Ni), Lead (Pb), Silicon (Si), Vanadium (V), and Zinc (Zn). The monitored data from approximately 600 locations were integrated with more than 160 predictors, such as time and location, satellite observations, composite predictors, meteorological covariates, and many novel land use variables using several machine learning algorithms and ensemble methods. Multiple machine-learning models were developed covering urban areas and non-urban areas. Their predictions were then ensembled using either a Generalized Additive Model (GAM) Ensemble Geographically-Weighted-Averaging (GAM-ENWA), or Super-Learners. The overall best model R-squared values for the test sets ranged from 0.79 for Copper to 0.88 for Zinc in non-urban areas. In urban areas, the R-squared model values ranged from 0.80 for Copper to 0.88 for Zinc. The Coordinate Reference System (CRS) used in the predictions is the World Geodetic System 1984 (WGS84) and the Units for the PM2.5 Components TEs are nanograms per cubic meter. The data are provided in RDS tabular format, a file format native to the R programming language, but can also be opened by other languages such as Python. proprietary CIESIN_SEDAC_CD_ADM_GIS_1990_1.01 China Dimensions Data Collection: China Administrative Regions GIS Data: 1:1M, County Level, 1990 SEDAC STAC Catalog 1990-12-31 1990-12-31 73, 18, 135, 54 https://cmr.earthdata.nasa.gov/search/concepts/C179001737-SEDAC.umm_json The China Administrative Regions GIS Data: 1:1M, County Level, 1990 consists of geographic boundary data for the administrative regions of China as of 31 December 1990. The data includes the geographical location, area, administrative division code, and county and island name. The data are at a scale of one to one million (1:1M) at the national, provincial, and county level. This data set is produced in collaboration with the Center for International Earth Science Information Network (CIESIN), Chinese Academy of Surveying and Mapping (CASM), and the University of Washington as part of the China in Time and Space (CITAS) project. proprietary CIESIN_SEDAC_CD_ADM_GIS_JUL90_1.00 China Dimensions Data Collection: China Administrative Regions GIS Data: 1:1M, County Level, 1 July 1990 SEDAC STAC Catalog 1990-07-01 1990-07-01 73, 18, 135, 54 https://cmr.earthdata.nasa.gov/search/concepts/C179001903-SEDAC.umm_json The China Administrative Regions GIS Data: 1:1M, County Level, 1 July 1990 consists of geographic boundary data for the administrative regions of China as of 1 July 1990. The data includes the geographical location, area, administrative division code, and county and island name. The data are at a scale of one to one million (1:1M) at the national, provincial, and county level. This data set is produced in collaboration with the Center for International Earth Science Information Network (CIESIN), Chinese Academy of Surveying and Mapping (CASM), and the University of Washington as part of the China in Time and Space (CITAS) project. proprietary CIESIN_SEDAC_CD_AGENDA21_1.00 China Dimensions Data Collection: Priority Programme for China's Agenda 21 SEDAC STAC Catalog 1993-01-01 1993-12-31 73, 18, 135, 54 https://cmr.earthdata.nasa.gov/search/concepts/C179001910-SEDAC.umm_json The Priority Programme for China's Agenda 21 consists of full-text program descriptions supporting China's economic and social development. The descriptions represent 69 programs covering legislation, policy, education, agriculture, environment, energy, transportation, regional development, population, health, and global change research. Each description includes project scope, background, objectives, activities, inputs, and benefits. This data set is produced in collaboration with the Administrative Center for China's Agenda 21 (ACCA21), United Nations Development Programme (UNDP), and the Columbia University Center for International Earth Science Information Network (CIESIN). proprietary @@ -6155,10 +6155,10 @@ GHISACONUS_001 Global Hyperspectral Imaging Spectral-library of Agricultural cro GIMMS3g_NDVI_Trends_1275_1 Long-Term Arctic Growing Season NDVI Trends from GIMMS 3g, 1982-2012 ORNL_CLOUD STAC Catalog 1982-06-01 2012-08-31 -180, 20, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784897341-ORNL_CLOUD.umm_json This data set provides normalized difference vegetation index (NDVI) data for the arctic growing season derived primarily with data from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard several NOAA satellites over the years 1982 through 2012. The NDVI data, which show vegetation activity, were averaged annually for the arctic growing season (GS; June, July and August). The products include the annual GS-NDVI values and the results of a cumulative GS-NDVI time series trends analysis. The data are circumpolar in coverage at 8-km resolution and limited to greater than 20 degrees N.These normalized difference vegetation index (NDVI) trends were calculated using the third generation data set from the Global Inventory Modeling and Mapping Studies (GIMMS 3g). GIMMS 3g improves on its predecessor (GIMMS g) in three important ways. First, GIMMS 3g integrates data from NOAA-17 and 18 satellites to lengthen its record. Second, it addresses the spatial discontinuity north of 72 degrees N, by using SeaWiFS, in addition to SPOT VGT, to calibrate between the second and third versions of the AVHRR sensor (AVHRR/2 and AVHRR/3). Finally, the GIMMS 3g algorithm incorporates improved snowmelt detection and is calibrated based on data from the shorter, arctic growing season (May-September) rather than the entire year (January-December). proprietary GISS-CMIP5_1 GISS ModelE2 contributions to the CMIP5 archive NCCS STAC Catalog 0850-01-01 2100-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1542315069-NCCS.umm_json We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980-2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics. proprietary GIS_EastAngliaClimateMonthly_551_1 Global Monthly Climatology for the Twentieth Century (New et al.) ORNL_CLOUD STAC Catalog 1900-01-01 1998-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2780535151-ORNL_CLOUD.umm_json A 0.5 degree lat/lon data set of monthly surface climate over global land areas, excluding Antarctica. Primary variables are interpolated directly from station time-series: precipitation, mean temperature and diurnal temperature range. proprietary -GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary -GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary +GLAH01_033 GLAS/ICESat L1A Global Altimetry Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product. proprietary GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary +GLAH02_033 GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153547514-NSIDC_CPRD.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary GLAH03_033 GLAS/ICESat L1A Global Engineering Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991863-NSIDC_ECS.umm_json Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02. proprietary GLAH04_033 GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing. proprietary @@ -6167,24 +6167,24 @@ GLAH05_034 GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V GLAH05_034 GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.umm_json GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization). Each data granule has an associated browse product. proprietary GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000445-NSIDC_ECS.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary GLAH06_034 GLAS/ICESat L1B Global Elevation Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.umm_json GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product. proprietary -GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549420-NSIDC_CPRD.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary -GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary +GLAH07_033 GLAS/ICESat L1B Global Backscatter Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991867-NSIDC_ECS.umm_json GLAH07 Level-1B global backscatter data are provided at full instrument resolution. The product includes full 532 nm (41.1 to -1.0 km) and 1064 nm (20 to -1 km) calibrated attenuated backscatter profiles at 5 times per second, and from 10 to -1 km, at 40 times per second for both channels. Also included are calibration coefficient values and molecular backscatter profiles at once per second. Data granules contain approximately 190 minutes (2 orbits) of data. Each data granule has an associated browse product. proprietary GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary +GLAH08_033 GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549511-NSIDC_CPRD.umm_json GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate). Each data granule has an associated browse product. proprietary GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary GLAH09_033 GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz. Each data granule has an associated browse product. proprietary -GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary +GLAH10_033 GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-09-25 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds. Each data granule has an associated browse product. proprietary GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C189991871-NSIDC_ECS.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary GLAH11_033 GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product. proprietary -GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH12_034 GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000464-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH13_034 GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000443-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary -GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH14_034 GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_ECS STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary +GLAH15_034 GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034 NSIDC_CPRD STAC Catalog 2003-02-20 2009-10-11 -180, -86, 180, 86 https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product. proprietary GLCHMK_001 G-LiHT Canopy Height Model KML V001 LPCLOUD STAC Catalog 2011-06-30 -170, 10, -50, 73 https://cmr.earthdata.nasa.gov/search/concepts/C2763264695-LPCLOUD.umm_json Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Canopy Height Model Keyhole Markup Language (KML) data product (GLCHMK) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed. GLCHMK data are processed as a Google Earth overlay KML file at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format. proprietary GLCHMT_001 G-LiHT Canopy Height Model V001 LPCLOUD STAC Catalog 2011-06-30 -170, 10, -50, 73 https://cmr.earthdata.nasa.gov/search/concepts/C2763264702-LPCLOUD.umm_json Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Canopy Height Model data product (GLCHMT) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed. GLCHMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format. proprietary GLDAS_CLM10SUBP_3H_001 GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H) at GES DISC GES_DISC STAC Catalog 1979-01-02 2020-03-31 -180, -60, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1279404074-GES_DISC.umm_json With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001. The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system. However, the replacement for GLDAS-001 monthly and 3-hourly 1.0 x 1.0 degree products from CLM Land Surface Model currently are not available yet. Once their replacement data products become available, the DOIs of GLDAS-001 CLM data products will direct to the GLDAS-2.1 CLM data products. This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly. This simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year. WGRIB or another GRIB reader is required to read the files. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For more information, please see the README document. proprietary @@ -9668,6 +9668,7 @@ MCD43D66_061 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF-Adjusted Ref Band5 Daily L3 MCD43D67_061 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF-Adjusted Ref Band6 Daily L3 Global 30ArcSec CMG V061 LPCLOUD STAC Catalog 2000-02-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2540275748-LPCLOUD.umm_json The MCD43D67 Version 6.1 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Nadir BRDF-Adjusted Reflectance (NBAR) dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter (m)) resolution. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name. This Climate Modeling Grid (CMG) product covers the entire globe for use in climate simulation models. Due to the large file size, each MCD43D product contains just one data layer. MCD43D62 through MCD43D68 are the NBAR products of the MCD43D BRDF/Albedo product suite for MODIS bands 1 through 7. The NBAR algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon. MCD43D67 is the NBAR for MODIS band 6. Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). proprietary MCD43D68_061 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF-Adjusted Ref Band7 Daily L3 Global 30ArcSec CMG V061 LPCLOUD STAC Catalog 2000-02-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2540275753-LPCLOUD.umm_json The MCD43D68 Version 6.1 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Nadir BRDF-Adjusted Reflectance (NBAR) dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter (m)) resolution. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name. This Climate Modeling Grid (CMG) product covers the entire globe for use in climate simulation models. Due to the large file size, each MCD43D product contains just one data layer. MCD43D62 through MCD43D68 are the NBAR products of the MCD43D BRDF/Albedo product suite for MODIS bands 1 through 7. The NBAR algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon. MCD43D68 is the NBAR for MODIS band 7. Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). proprietary MCD43GF_006 MODIS/Terra+Aqua BRDF/Albedo Gap-Filled Snow-Free Daily L3 Global 30ArcSec CMG V006 LPDAAC_ECS STAC Catalog 2000-03-03 2017-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1623882456-LPDAAC_ECS.umm_json "The Daily Moderate Resolution Imaging Spectroradiometer (MODIS) (Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) 30 arc second, Global Gap-Filled, Snow-Free, (MCD43GF) Version 6 is derived from the 30 arc second Climate Modeling Grid (CMG) MCD43D Version 6 product suite, with additional processing to provide a gap-filled, snow-free product. The highest quality full inversion values were used for the temporal fitting effort and supplemented with lower quality pixels, spatial fitting, and spatial smoothing as needed. The status of each pixel can be found in the quality layer for each band. To generate a snow-free product, pixels with ephemeral snow were removed using the MCD43D41 (https://doi.org/10.5067/MODIS/MCD43D41.006) snow flags. The underlying MCD43D utilizes a BRDF model derived from all available high quality cloud clear reflectance data over a 16 day moving window centered on and emphasizing the daily day of interest (the ninth day of each retrieval period as reflected in the Julian date in the filename). This 30arc second BRDF model is then used to produce the Albedo and NBAR products (MCD43D). These BRDF model parameters are computed for MODIS spectral bands 1 through 7 (0.47 um, 0.55 um, 0.67 um, 0.86 um, 1.24 um, 1.64 um, 2.1 um), as well as the shortwave infrared band (0.3-5.0um), visible band (0.3-0.7 um), and near-infrared (0.7-5.0 um) broad bands. The MCD43GF product includes 67 layers containing black-sky albedo (BSA) at local solar noon, isotropic (ISO), volumetric (VOL), geometric (GEO), quality (QA), Nadir BRDF-Adjusted Reflectance (NBAR) at local solar noon, and white-sky albedo (WSA). Due to the large file size, each data layer is distributed as a separate HDF file. Users are encouraged to download the quality layers for each of the 10 bands to check quality assessment information before using the BRDF/Albedo data. Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications (https://www.umb.edu/spectralmass/terra_aqua_modis/v006). The MCD43 product is not recommended for solar zenith angles beyond 70 degrees. The MODIS BRDF/Albedo products have achieved stage 3 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation. Improvements/Changes from Previous Versions Observations are weighted to estimate the BRDF/Albedo on the ninth day of the 16-day period. * MCD43 products use the snow status weighted to the ninth day instead of the majority snow/no-snow observations from the 16-day period. * Better quality at high latitudes from use of all available observations for the acquisition period. Collection 5 used only four observations per day. * The MCD43 products use L2G-lite surface reflectance as input. * In cases where insufficient high-quality reflectances are obtained, a database with archetypal BRDF parameters is used to supplement the observational data and perform a lower quality magnitude inversion. This database is continually updated with the latest full inversion retrieval for each pixel. * CMG Albedo is estimated using all the clear-sky observations within the 1,000 m grid as opposed to aggregating from the 500 m albedo. Important Quality Information The incorrect representation of the aerosol quantities (low average high) in the C6 MYD09 and MOD09 surface reflectance products may have impacted down stream products particularly over arid bright surfaces (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/displayCase.cgi?esdt=MOD09&caseNum=PM_MOD09_20010&caseLocation=cases_data&type=C6). This (and a few other issues) have been corrected for C6.1. Therefore users should avoid substantive use of the C6 MCD43 products and wait for the C6.1 products. In any event, users are always strongly encouraged to download and use the extensive QA data provided in MCD43A2, in addition to the briefer mandatory QAs provided as part of the MCD43A1, 3, and 4 products. " proprietary +MCD43GF_061 MODIS/Terra+Aqua BRDF/Albedo Gap-Filled Snow-Free Daily L3 Global 30ArcSec CMG V061 LPCLOUD STAC Catalog 2000-03-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3216719281-LPCLOUD.umm_json The Daily Moderate Resolution Imaging Spectroradiometer (MODIS) (Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) 30 arc second, Global Gap-Filled, Snow-Free, (MCD43GF) Version 6.1 is derived from the 30 arc second Climate Modeling Grid (CMG) MCD43D Version 6.1 product suite, with additional processing to provide a gap-filled, snow-free product. The highest quality full inversion values were used for the temporal fitting effort and supplemented with lower quality pixels, spatial fitting, and spatial smoothing as needed. The status of each pixel can be found in the quality layer for each band. To generate a snow-free product, pixels with ephemeral snow were removed using the [MCD43D41](https://doi.org/10.5067/MODIS/MCD43D41.061) snow flags. The underlying MCD43D utilizes a BRDF model derived from all available high quality cloud clear reflectance data over a 16 day moving window centered on and emphasizing the daily day of interest (the ninth day of each retrieval period as reflected in the Julian date in the filename). This 30 arc second BRDF model is then used to produce the Albedo and NBAR products (MCD43D). These BRDF model parameters are computed for MODIS spectral bands 1 through 7 (0.47 um, 0.55 um, 0.67 um, 0.86 um, 1.24 um, 1.64 um, 2.1 um), as well as the shortwave infrared band (0.3-5.0 um), visible band (0.3-0.7 um), and near-infrared (0.7-5.0 um) broad bands. The MCD43GF product includes 67 layers containing black-sky albedo (BSA) at local solar noon, isotropic model parameter (ISO), volumetric model parameter (VOL), geometric model parameter (GEO), quality (QA), Nadir BRDF-Adjusted Reflectance (NBAR) at local solar noon, and white-sky albedo (WSA). Due to the large file size, each data layer is distributed as a separate HDF file. Users are encouraged to download the quality layers for each of the 10 bands to check quality assessment information before using the BRDF/Albedo data. The MCD43 product is not recommended for solar zenith angles beyond 70 degrees. Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the [User Guide](https://www.umb.edu/spectralmass/modis-user-guide-v006-and-v0061/mcd43gf-cmg-gap-filled-snow-free-products/). Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * In Version 6.1 reprocessing, the QA values for the MCD43GF product will change to reflect the band 5 and 6 dead detector issues. proprietary MCD64A1_061 MODIS/Terra+Aqua Direct Broadcast Burned Area Monthly L3 Global 500m SIN Grid V061 LPCLOUD STAC Catalog 2000-11-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2565786756-LPCLOUD.umm_json The Terra and Aqua combined MCD64A1 Version 6.1 Burned Area data product is a monthly, global gridded 500 meter (m) product containing per-pixel burned-area and quality information. The MCD64A1 burned-area mapping approach employs 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance imagery coupled with 1 kilometer (km) MODIS active fire observations. The algorithm uses a burn sensitive Vegetation Index (VI) to create dynamic thresholds that are applied to the composite data. The VI is derived from MODIS shortwave infrared atmospherically corrected surface reflectance bands 5 and 7 with a measure of temporal texture. The algorithm identifies the date of burn for the 500 m grid cells within each individual MODIS tile. The date is encoded in a single data layer as the ordinal day of the calendar year on which the burn occurred with values assigned to unburned land pixels and additional special values reserved for missing data and water grid cells. The data layers provided in the MCD64A1 product include Burn Date, Burn Data Uncertainty, Quality Assurance, along with First Day and Last Day of reliable change detection of the year. Validation at stage 3 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Burned Area product. Further details regarding MODIS land product validation for the MCD64A1 data product is available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MOD64). Improvements/Changes from Previous Versions * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). proprietary MCDAODHD_6.1NRT MODIS/Terra+Aqua L3 Value-added Aerosol Optical Depth - NRT LANCEMODIS STAC Catalog 2017-10-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426395436-LANCEMODIS.umm_json MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its 2330 km viewing swath width provides almost daily global coverage. It acquires data in 36 high spectral resolution bands between 0.415 to 14.235 micron with spatial resolutions of 250m(2 bands), 500m(5 bands),and 1000m (29 bands). MODIS sensor counts, calibrated radiances, geolocation products and all derived geophysical atmospheric and ocean products are archived at various DAACs and has been made available to public since April 2000. The shortname for this level-3 MODIS aerosol product is MCDAODHD. The Naval Research Laboratory and the University of North Dakota developed this value-added aerosol optical depth dataset based on MODIS Level 2 aerosol products. MCDAODHD is a gridded product and is specifically designed for quantitative applications including data assimilation and model validation. It is available through LANCE-MODIS. It offers several enhancements over the MODIS Level 2 data on which it is based. These enhancements include stringent filtering to reduce outliers, eliminate cloud contamination, and exclude conditions where aerosol detection is likely to be inaccurate; reduction of systematic biases over land and ocean by empirical corrections; reduction of random variation in AOD values by spatial averaging; quantitative estimation of uncertainty for each AOD data point. The MxDAODHD granules are produced every six hours, and time-stamped 00:00, 06:00, 12:00, and 18:00 (all times UTC). Each granule includes MODIS observations from +/-3 hours from the timestamp (e.g. 12:00 product includes MODIS data from 09:00-15:00 UTC). Production is initiated as soon as the Level 2 inputs become available in the LANCE system. See the LANCE-MODIS page for more dataset information: https://earthdata.nasa.gov/earth-observation-data/near-real-time/download-nrt-data/modis-nrt proprietary MCDONALD_QUICKBIRD_GIS_1 McDonald Islands - Data digitised from Quickbird satellite imagery aquired 9 April 2003. AU_AADC STAC Catalog 2003-04-09 2003-04-09 72.56401, -53.06268, 72.62856, -53.01065 https://cmr.earthdata.nasa.gov/search/concepts/C1214313642-AU_AADC.umm_json Coastline, ridgelines and areas of bare rock of McDonald Islands were digitised from Quickbird satellite imagery acquired 9 April 2003. proprietary @@ -9805,9 +9806,9 @@ MIANTASC_002 MISR TASC dataset V002 LARC STAC Catalog 1999-12-18 -180, -90, 180 MIB1LM_002 MISR Level 1B1 Local Mode Radiance Data V002 LARC STAC Catalog 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031461-LARC.umm_json This is the Local Mode Level 1B1 Product containing the DNs radiometrically scaled to radiances with no geometric resampling proprietary MIB2GEOP_002 MISR Geometric Parameters V002 LARC STAC Catalog 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C43677702-LARC.umm_json Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Geometric Parameters V002 contains the Geometric Parameters which measure the sun and view angles at the reference ellipsoid proprietary MIB2GEOP_003 MISR Geometric Parameters V003 LARC STAC Catalog 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2794387069-LARC.umm_json MIB2GEOP_003 is the Multi-angle Imaging SpectroRadiometer (MISR) Geometric Parameters Version 3 product. It contains the Geometric Parameters which measure the sun and view angles at the reference ellipsoid. Data collection for this product is ongoing. The distribution format of this product is NetCDF-4 which is a migration from the previous version's format of HDF-EOS2. MISR itself is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the affects of sunlight on Earth, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. proprietary -MICASA_FLUX_3H_1 MiCASA 3-hourly NPP NEE Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2023-12-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273640138-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary -MICASA_FLUX_D_1 MiCASA Daily NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2023-12-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273639213-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary -MICASA_FLUX_M_1 MiCASA Monthly NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2023-12-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273638632-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary +MICASA_FLUX_3H_1 MiCASA 3-hourly NPP NEE Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2024-07-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273640138-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary +MICASA_FLUX_D_1 MiCASA Daily NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2024-07-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273639213-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary +MICASA_FLUX_M_1 MiCASA Monthly NPP Rh ATMC NEE FIRE FUEL Fluxes 0.1 degree x 0.1 degree GES_DISC STAC Catalog 2001-01-01 2024-07-31 -180, -90, 179, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3273638632-GES_DISC.umm_json MiCASA is an extensive revision of CASA-GFED3. CASA-GFED3 derives from Potter et al. (1993), diverging in development since Randerson et al. (1996). CASA is a light use efficiency model: NPP is expressed as the product of photosynthetically active solar radiation, a light use efficiency parameter, scalars that capture temperature and moisture limitations, and fractional absorption of photosynthetically active radiation (fPAR) by the vegetation canopy derived from satellite data. Fire parameterization was incorporated into the model by van der Werf et al. (2004) leading to CASA-GFED3 after several revisions (van der Werf et al., 2006, 2010). Development of the GFED module has continued, now at GFED5 (Chen et al., 2023) with less focus on the CASA module. MiCASA diverges from GFED development at version 3, although future reconciliation is possible. Input datasets include air temperature, precipitation, incident solar radiation, a soil classification map, and several satellite derived products. These products are primarily based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined datasets including land cover classification (MCD12Q1), burned area (MCD64A1), Nadir BRDF-Adjusted Reflectance (NBAR; MCD43A4), from which fPAR is derived, and tree/herbaceous/bare vegetated fractions from Terra only (MOD44B). Emissions due to fire and burning of coarse woody debris (fuel wood) are estimated separately. proprietary MICRONESIAN_0 Measurements stretching across the Pacific Ocean to the Hawaiian Islands from 1998 to 1999 OB_DAAC STAC Catalog 1998-09-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360482-OB_DAAC.umm_json Measurements made primarily in Micronesia, but stretching across the Pacific Ocean to the Hawaiian Islands from 1998 to 1999. proprietary MIL1A_2 MISR Level 1A CCD Science data, all cameras V002 LARC STAC Catalog 2018-05-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031533-LARC.umm_json MIL1A_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 1A CCD Science data, all cameras version 2. It is the Reformatted Annotated Level 1A product for the CCD science data. The data numbers (DN) have been commuted from 12-bit numbers to 16-bit byte aligned half-words. The MISR CCD Science Instrument Data acquired from all nine of the MISR cameras for each of the four bands represent the raw MISR input data staged for MISR Science Instrument Data processing. There are nine file granules of this type, one corresponding to each of the nine MISR cameras. Each file granule contains four entire swaths of data, one swath for each of the four MISR bands associated with each MISR camera. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. proprietary MIL2ASAE_002 MISR Level 2 Aerosol parameters V002 LARC STAC Catalog 2000-02-24 2017-06-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C43677706-LARC.umm_json Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Level 2 Aerosol parameters V002 contains Aerosol optical depth and particle type, with associated atmospheric data. proprietary @@ -11762,13 +11763,13 @@ P6_AWIF_STUC00GTD_1.0 Resourcesat-1 AWIFS Standard Products ISRO STAC Catalog 20 P6_LIS3_STUC00GTD_1.0 Resourcesat-1 LIS3 Standard Products ISRO STAC Catalog 2003-12-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1373228023-ISRO.umm_json The medium resolution multi-spectral sensor, LISS-3 operates in four spectral bands - B2, B3, B4 in visible near infrared (VNIR) and B5 in Short Wave Infrared (SWIR) providing data with 23.5m resolution. Standard products are full scene (path-row) based geo-referenced as well as geo-orthokit products. proprietary PACE-PAX_0 The Plankton, Aerosol, Cloud, ocean Ecosystem Postlaunch Airborne eXperiment OB_DAAC STAC Catalog 2024-08-01 2024-10-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3268194735-OB_DAAC.umm_json PACE-PAX SeaBASS DOI description: The Plankton, Aerosol, Cloud, ocean Ecosystem Postlaunch Airborne eXperiment (PACE-PAX) was a field campaign to support validation of the PACE mission through a combination of multiple platforms including aircraft (ER-2, CIRPAS Twin Otter), ships (R/V Shearwater, R/V Blissfully), autonomous ocean- and land-based instruments, and collaboration with the PACE Validation Science Teams (e.g.PVST-SBCR and PVST-CALCOFI) and PACE Vicarious Calibration systems (HyperNAV). The PACE-PAX mission took place during the month of September 2024 in Southern and Central California and nearby coastal regions. All PACE-PAX data are to be archived in 3 main data repositories: (1) NASA AIR-LARC for all aircraft data (until final data submission in March 2025 then migrated to the Langley Airborne DAAC), (2) AERONET-MAN for Microtops data, and (3) SeaBASS for all ocean optical, biogeochemical and phytoplankton data. The SeaBASS PACE-PAX DOI is split into 4 main cruises: PACE-PAX_Shearwater (cruise_id=RFDDMM-RS), PACE-PAX_Blissfully (cruise_id=RFDDMM-RB), PACE-PAX_SBCR (cruise_id=RFMMDD-SB), PACE-PAX_CALCOFI (cruise_id=RFMMDD-CL) where DDMM, represent the day and month collection date. proprietary PACE_ABSclosure_0 PACE Absorbance Closure project, Florida OB_DAAC STAC Catalog 2017-01-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360584-OB_DAAC.umm_json Measurements from the PACE Absorbance Closure project off the coast of Florida. proprietary -PACE_EPH_DEF_1 PACE Definitive Ephemeris Data Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020918309-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary -PACE_HARP2_L0_1 PACE HARP2 Level-0 Instrument Telemetry/Multi-Detector Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HARP2_L0_D1_1 PACE HARP2 Level-0 Detector 1 (D1) Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HARP2_L0_D2_1 PACE HARP2 Level-0 Detector 2 (D2) Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HARP2_L0_D3_1 PACE HARP2 Level-0 Detector 3 (D3) Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HARP2_L0_REAL_1 PACE HARP2 Level-0 Real-time Direct Transfer Mode Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HARP2_L0_SCI_1 PACE HARP2 Level-0 Science Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_EPH_DEF_1 PACE Definitive Ephemeris Data Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020918309-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary +PACE_HARP2_L0_1 PACE HARP2 Level-0 Instrument Telemetry/Multi-Detector Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_HARP2_L0_D1_1 PACE HARP2 Level-0 Detector 1 (D1) Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_HARP2_L0_D2_1 PACE HARP2 Level-0 Detector 2 (D2) Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_HARP2_L0_D3_1 PACE HARP2 Level-0 Detector 3 (D3) Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_HARP2_L0_REAL_1 PACE HARP2 Level-0 Real-time Direct Transfer Mode Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary +PACE_HARP2_L0_SCI_1 PACE HARP2 Level-0 Science Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary PACE_HARP2_L1A_AST0_2 PACE HARP2 Level-1A Acquisition Scheme Type 0 - Full-Resolution Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026579577-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary PACE_HARP2_L1A_AST1_2 PACE HARP2 Level-1A Acquisition Scheme Type 1 - Half-Resolution Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026579667-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary PACE_HARP2_L1A_AST2_2 PACE HARP2 Level-1A Acquisition Scheme Type 2 -  Science Mode (no MTDI) Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026579735-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary @@ -11779,20 +11780,20 @@ PACE_HARP2_L1B_AST4_2 PACE HARP2 Level-1B Acquisition Scheme Type 4 - Science Mo PACE_HARP2_L1B_SCI_2 PACE HARP2 Level-1B Science Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026580118-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary PACE_HARP2_L1C_AST4_2 PACE HARP2 Level-1C Acquisition Scheme Type 4 - Science Mode Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026580193-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary PACE_HARP2_L1C_SCI_2 PACE HARP2 Level-1C Science Data, V2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026580280-OB_CLOUD.umm_json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument, flying aboard the PACE spacecraft, is a wide-angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. proprietary -PACE_HKT_1 PACE Spacecraft Housekeeping, NetCDF format Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2832273136-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary -PACE_HSK_1 PACE Spacecraft Housekeeping Data, V1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2869693107-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary -PACE_OCI_L0_DARK_1 PACE OCI Level-0 Dark Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798299-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_DIAG_1 PACE OCI Level-0 Diagnostic/Calibaration Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798302-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_LIN_1 PACE OCI Level-0 Linearity Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798304-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_LUN_1 PACE OCI Level-0 Lunar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798306-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_RAW_1 PACE OCI Level-0 Raw Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798308-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SCI_1 PACE OCI Level-0 Science Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798309-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SNAPI_1 PACE OCI Level-0 Snapshot Internal Trigger Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798315-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SNAPX_1 PACE OCI Level-0 Snapshot External Trigger Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798322-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SOLD_1 PACE OCI Level-0 Daily Solar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798329-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SOLM_1 PACE OCI Level-0 Monthly Solar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798338-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_SPEC_1 PACE OCI Level-0 Spectral Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798347-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary -PACE_OCI_L0_STAT_1 PACE OCI Level-0 Static Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798354-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_HKT_1 PACE Spacecraft Housekeeping, NetCDF format Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2832273136-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary +PACE_HSK_1 PACE Spacecraft Housekeeping Data, V1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2869693107-OB_CLOUD.umm_json The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission launched in February 2024. The mission will carry three instruments - one hyperspectral radiometer (OCI) and two multi-angle polarimeters (HARP2 and SPEXone). The range that PACE's instruments will observe includes the UV (350-400 nm), visible (400-700 nm), and near infrared (700-885 nm), as well as several shortwave infrared bands. proprietary +PACE_OCI_L0_DARK_1 PACE OCI Level-0 Dark Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798299-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_DIAG_1 PACE OCI Level-0 Diagnostic/Calibaration Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798302-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_LIN_1 PACE OCI Level-0 Linearity Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798304-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_LUN_1 PACE OCI Level-0 Lunar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798306-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_RAW_1 PACE OCI Level-0 Raw Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798308-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SCI_1 PACE OCI Level-0 Science Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798309-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SNAPI_1 PACE OCI Level-0 Snapshot Internal Trigger Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798315-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SNAPX_1 PACE OCI Level-0 Snapshot External Trigger Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798322-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SOLD_1 PACE OCI Level-0 Daily Solar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798329-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SOLM_1 PACE OCI Level-0 Monthly Solar Calibration Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798338-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_SPEC_1 PACE OCI Level-0 Spectral Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798347-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary +PACE_OCI_L0_STAT_1 PACE OCI Level-0 Static Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798354-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary PACE_OCI_L1A_SCI_2 PACE OCI Level-1A Science Data, version 2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026581050-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary PACE_OCI_L1B_SCI_2 PACE OCI Level-1B Science Data, version 2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026581092-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary PACE_OCI_L1C_SCI_2 PACE OCI Level-1C Science Data, version 2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026581150-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary @@ -11900,7 +11901,7 @@ PACE_OCI_L3M_RRS_2.0 PACE OCI Level-3 Global Mapped Remote-Sensing Reflectance ( PACE_OCI_L3M_RRS_NRT_2.0 PACE OCI Level-3 Global Mapped Remote-Sensing Reflectance (RRS) - NRT Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020924646-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary PACE_OCI_L3M_SFREFL_2.0 PACE OCI Level-3 Global Mapped Surface Reflectance Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020924782-OB_CLOUD.umm_json The primary sensor aboard the PACE spacecraft is the Ocean Color Instrument (OCI). It is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. proprietary PACE_OCI_L3M_SFREFL_NRT_2.0 PACE OCI Level-3 Global Mapped Surface Reflectance - Near Real-time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020924734-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary -PACE_SPEXONE_L0_1 PACE SPEXone Level-0 Data, version 1 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2816780240-OB_CLOUD.umm_json The Spectro-polarimeter for Planetary Exploration one (SPEXone) instrument flying aboard the PACE spacecraft is a multi-angle polarimeter. It measures the intensity, Degree of Linear Polarization (DoLP) and Angle of Linear Polarization (AoLP) of sunlight reflected back from Earth's atmosphere, land surface, and ocean. The focus of the SPEXone development is to achieve a very high accuracy of DoLP measurements, which facilitates accurate characterization of aerosols in the atmosphere. proprietary +PACE_SPEXONE_L0_1 PACE SPEXone Level-0 Data, version 1 OB_CLOUD STAC Catalog 2024-02-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2816780240-OB_CLOUD.umm_json The Spectro-polarimeter for Planetary Exploration one (SPEXone) instrument flying aboard the PACE spacecraft is a multi-angle polarimeter. It measures the intensity, Degree of Linear Polarization (DoLP) and Angle of Linear Polarization (AoLP) of sunlight reflected back from Earth's atmosphere, land surface, and ocean. The focus of the SPEXone development is to achieve a very high accuracy of DoLP measurements, which facilitates accurate characterization of aerosols in the atmosphere. proprietary PACE_SPEXONE_L1A_SCI_2 PACE SPEXone Level-1A Science Data, version 2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026586666-OB_CLOUD.umm_json The Spectro-polarimeter for Planetary Exploration one (SPEXone) instrument flying aboard the PACE spacecraft is a multi-angle polarimeter. It measures the intensity, Degree of Linear Polarization (DoLP) and Angle of Linear Polarization (AoLP) of sunlight reflected back from Earth's atmosphere, land surface, and ocean. The focus of the SPEXone development is to achieve a very high accuracy of DoLP measurements, which facilitates accurate characterization of aerosols in the atmosphere. proprietary PACE_SPEXONE_L1B_SCI_2 PACE SPEXone Level-1B Science Data, version 2 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3026586707-OB_CLOUD.umm_json The Spectro-polarimeter for Planetary Exploration one (SPEXone) instrument flying aboard the PACE spacecraft is a multi-angle polarimeter. It measures the intensity, Degree of Linear Polarization (DoLP) and Angle of Linear Polarization (AoLP) of sunlight reflected back from Earth's atmosphere, land surface, and ocean. The focus of the SPEXone development is to achieve a very high accuracy of DoLP measurements, which facilitates accurate characterization of aerosols in the atmosphere. proprietary PACE_SPEXONE_L1B_SCI_3 PACE SPEXone Level-1B Science Data, version 3 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3285304315-OB_CLOUD.umm_json The Spectro-polarimeter for Planetary Exploration one (SPEXone) instrument flying aboard the PACE spacecraft is a multi-angle polarimeter. It measures the intensity, Degree of Linear Polarization (DoLP) and Angle of Linear Polarization (AoLP) of sunlight reflected back from Earth's atmosphere, land surface, and ocean. The focus of the SPEXone development is to achieve a very high accuracy of DoLP measurements, which facilitates accurate characterization of aerosols in the atmosphere. proprietary @@ -13742,11 +13743,13 @@ TROPICS01ANTTL1A_1.0 TROPICS01 Pathfinder L1A Orbital Geolocated Native-Resolu TROPICS01BRTTL1B_1.0 TROPICS01 Pathfinder L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2622841366-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS01MIRSL2B_1.0 TROPICS01 Pathfinder L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2929021086-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the Pathfinder satellite, as the full version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS01PRPSL2B_1.0 TROPICS01 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3104593940-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the Pathfinder satellite, as the full version of the Level 1a geolocated antenna temperatures (radiance) in units of kelvins that are timestamped to UTC and are reported at native spatial resolutions. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary +TROPICS01TCIEL2B_1.0 TROPICS01 Pathfinder L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3280791029-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023." proprietary TROPICS01URADL2A_1.0 TROPICS01 Pathfinder L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859214263-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the Pathfinder satellite, as the provisional version of the Level 2A geolocated brightness temperature that are reported at native spatial resolutions. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS03ANTTL1A_1.0 TROPICS03 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499152-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS03BRTTL1B_1.0 TROPICS03 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499529-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS03MIRSL2B_0.2 TROPICS03 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2857802936-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary TROPICS03PRPSL2B_1.0 TROPICS03 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary +TROPICS03TCIEL2B_1.0 TROPICS03 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3279630448-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023." proprietary TROPICS03URADL2A_1.0 TROPICS03 L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3179859133-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS05ANTTL1A_0.2 TROPICS05 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2985158466-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. " proprietary TROPICS05BRTTL1B_0.2 TROPICS05 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2985145021-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. " proprietary @@ -13756,6 +13759,7 @@ TROPICS06ANTTL1A_1.0 TROPICS06 L1A Orbital Geolocated Native-Resolution Antenna TROPICS06BRTTL1B_1.0 TROPICS06 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3171499970-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS06MIRSL2B_0.2 TROPICS06 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2857801590-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary TROPICS06PRPSL2B_1.0 TROPICS06 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details." proprietary +TROPICS06TCIEL2B_1.0 TROPICS06 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3280808959-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) to estimate the TC intensity. This validated TCIE data release starts in June 2023." proprietary TROPICS06URADL2A_1.0 TROPICS06 L2A Unified Resolution Brightness Temperatures V1.0 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3179860505-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is from the TROPICS06 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS07ANTTL1A_0.2 TROPICS07 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3104586410-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary TROPICS07BRTTL1B_0.2 TROPICS07 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V0.2 GES_DISC STAC Catalog 2021-07-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3104588185-GES_DISC.umm_json "The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data." proprietary