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Burn Scar example for Sentinel-2 NRT (#89)
* Add a dNBR example * Finish thumbnail work and some broader fixes. * Add GM indexing * Local dev environment simple dNBR * Implements 3-band nDBR transform with example * Resolve linting errors, update burnscar example configuration * Remove empty section Co-authored-by: Alex Leith <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,138 @@ | ||
| from typing import Dict | ||
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| import numpy | ||
| from datacube import Datacube | ||
| from datacube.virtual import Measurement, Transformation | ||
| from xarray import Dataset, merge | ||
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| class DeltaNBR(Transformation): | ||
| """Return NBR""" | ||
|
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| def __init__(self): | ||
| self.output_measurements = { | ||
| "dnbr": {"name": "dnbr", "dtype": "float", "nodata": -9999, "units": ""} | ||
| } | ||
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| def measurements(self, input_measurements) -> Dict[str, Measurement]: | ||
| return self.output_measurements | ||
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| def compute(self, data) -> Dataset: | ||
| base_year = data.time.dt.year.values[0] - 1 | ||
| if base_year == 2021: | ||
| base_year = 2020 | ||
| if base_year == 2012: | ||
| base_year = 2013 | ||
|
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| dc = Datacube() | ||
| gm_data = dc.load( | ||
| product="ls8_nbart_geomedian_annual", | ||
| time=str(base_year), | ||
| like=data.geobox, | ||
| measurements=["nir", "swir2"], | ||
| ) | ||
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| pre = (gm_data.nir - gm_data.swir2) / (gm_data.nir + gm_data.swir2) | ||
| data = merge([data, {"pre": pre.isel(time=0, drop=True)}]) | ||
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| data["post"] = (data.nir - data.swir2) / (data.nir + data.swir2) | ||
| data["dnbr"] = data.pre - data.post | ||
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| data["dnbr"] = data.dnbr.where(data.nir != -999).astype(numpy.single) | ||
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| data = data.drop(["nir", "swir2", "pre", "post"]) | ||
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| return data | ||
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| class DeltaNBR_3band(Transformation): | ||
| """Return 3-Band NBR""" | ||
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| def __init__(self): | ||
| self.output_measurements = { | ||
| "delta_nbr": { | ||
| "name": "dnbr", | ||
| "dtype": "float", | ||
| "nodata": -9999, | ||
| "units": "", | ||
| }, | ||
| "delta_bsi": { | ||
| "name": "bsi", | ||
| "dtype": "float", | ||
| "nodata": -9999, | ||
| "units": "", | ||
| }, | ||
| "delta_ndvi": { | ||
| "name": "ndvi", | ||
| "dtype": "float", | ||
| "nodata": -9999, | ||
| "units": "", | ||
| }, | ||
| } | ||
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| def measurements(self, input_measurements) -> Dict[str, Measurement]: | ||
| return self.output_measurements | ||
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| def compute(self, data) -> Dataset: | ||
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| """ | ||
| Implementation ported from https://github.com/daleroberts/nrt-predict/blob/main/nrtmodels/burnscar.py#L39 | ||
| """ | ||
|
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| gm_base_year = data.time.dt.year.values[0] - 1 | ||
| if gm_base_year == 2021: | ||
| gm_base_year = 2020 | ||
| if gm_base_year == 2012: | ||
| gm_base_year = 2013 | ||
|
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| dc = Datacube() | ||
| gm_data = dc.load( | ||
| product="ls8_nbart_geomedian_annual", | ||
| time=str(gm_base_year), | ||
| like=data.geobox, | ||
| measurements=["blue", "red", "nir", "swir2"], # B02, B04, B08, B11 | ||
| ) | ||
|
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| # Delta Normalised Burn Ratio (dNBR) = (B08 - B11)/(B08 + B11) | ||
| pre_nbr = (gm_data.nir - gm_data.swir2) / (gm_data.nir + gm_data.swir2) | ||
| data = merge([data, {"pre_nbr": pre_nbr.isel(time=0, drop=True)}]) | ||
| data["post_nbr"] = (data.nir - data.swir2) / (data.nir + data.swir2) | ||
| data["delta_nbr"] = data.pre_nbr - data.post_nbr | ||
| data["delta_nbr"] = data.delta_nbr.where(data.nir != -999).astype(numpy.single) | ||
|
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| # Burn Scar Index (BSI) = ((B11 + B04) - (B08 - B02)) / ((B11 + B04) + (B08 - B02)) | ||
| pre_bsi = ((gm_data.swir2 + gm_data.red) - (gm_data.nir - gm_data.blue)) / ( | ||
| (gm_data.swir2 + gm_data.red) + (gm_data.nir - gm_data.blue) | ||
| ) | ||
| data = merge([data, {"pre_bsi": pre_bsi.isel(time=0, drop=True)}]) | ||
| data["post_bsi"] = ((data.swir2 + data.red) - (data.nir - data.blue)) / ( | ||
| (data.swir2 + data.red) + (data.nir - data.blue) | ||
| ) | ||
| data["delta_bsi"] = data.pre_bsi - data.post_bsi | ||
| data["delta_bsi"] = data.delta_bsi.where(data.nir != -999).astype(numpy.single) | ||
|
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| # Normalized Difference Vegetation Index (NDVI) = (B08 - B04)/(B08 + B04) | ||
| pre_ndvi = (gm_data.nir - gm_data.red) / (gm_data.nir + gm_data.red) | ||
| data = merge([data, {"pre_ndvi": pre_ndvi.isel(time=0, drop=True)}]) | ||
| data["post_ndvi"] = (data.nir - data.red) / (data.nir + data.red) | ||
| data["delta_ndvi"] = data.post_ndvi - data.pre_ndvi | ||
| data["delta_ndvi"] = data.delta_ndvi.where(data.nir != -999).astype( | ||
| numpy.single | ||
| ) | ||
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| data = data.drop( | ||
| [ | ||
| "nir", | ||
| "swir2", | ||
| "red", | ||
| "blue", | ||
| "post_nbr", | ||
| "pre_nbr", | ||
| "pre_bsi", | ||
| "post_bsi", | ||
| "pre_ndvi", | ||
| "post_ndvi", | ||
| ] | ||
| ) | ||
|
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||
| return data |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,43 @@ | ||
| specification: | ||
| products: | ||
| - s2a_nrt_granule | ||
| - s2b_nrt_granule | ||
| measurements: ['nbart_nir_1', 'nbart_red_edge_1'] | ||
| measurement_renames: | ||
| nbart_nir_1: nir | ||
| nbart_red_edge_1: swir2 | ||
|
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| aws_unsigned: True | ||
| transform: datacube_alchemist.transforms.DeltaNBR | ||
| transform_args: | ||
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| override_product_family: ard | ||
| basis: nbart_nir_1 | ||
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| output: | ||
| location: /tmp/alchemist | ||
| preview_image: | ||
| red: dnbr | ||
| green: dnbr | ||
| blue: dnbr | ||
| static_stretch: [-1, 1] | ||
| explorer_url: https://explorer.dev.dea.ga.gov.au | ||
| write_data_settings: | ||
| overview_resampling: average | ||
| reference_source_dataset: True | ||
| write_stac: True | ||
| inherit_geometry: True | ||
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| metadata: | ||
| product_family: dnbr | ||
| producer: ga.gov.au | ||
| dataset_version: 0.0.2 | ||
| collection_number: 3 | ||
| naming_conventions: dea_c3 | ||
| properties: | ||
| dea:dataset_maturity: interim | ||
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| processing: | ||
| dask_chunks: | ||
| x: -1 | ||
| y: 4096 |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,44 @@ | ||
| specification: | ||
| products: | ||
| - s2a_nrt_granule | ||
| - s2b_nrt_granule | ||
| measurements: ['nbart_nir_1', 'nbart_red_edge_1', 'nbart_blue', 'nbart_red'] | ||
| measurement_renames: | ||
| nbart_nir_1: nir | ||
| nbart_red_edge_1: swir2 | ||
| nbart_blue: blue | ||
| nbart_red: red | ||
|
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| aws_unsigned: True | ||
| transform: datacube_alchemist.transforms.DeltaNBR_3band | ||
|
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| override_product_family: ard | ||
| basis: nbart_nir_1 | ||
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| output: | ||
| location: /tmp/alchemist | ||
| preview_image: | ||
| red: delta_nbr | ||
| green: delta_ndvi | ||
| blue: delta_bsi | ||
| static_stretch: [-1, 1] | ||
| explorer_url: https://explorer.dev.dea.ga.gov.au | ||
| write_data_settings: | ||
| overview_resampling: average | ||
| reference_source_dataset: True | ||
| write_stac: True | ||
| inherit_geometry: True | ||
|
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| metadata: | ||
| product_family: bs | ||
| producer: ga.gov.au | ||
| dataset_version: 1.6.0 | ||
| collection_number: 3 | ||
| naming_conventions: dea_c3 | ||
| properties: | ||
| dea:dataset_maturity: interim | ||
|
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||
| processing: | ||
| dask_chunks: | ||
| x: -1 | ||
| y: 4096 |
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