Important
This project is currently under heavy development. Methods and results are still preliminary and subject to change.
This project generates statistics on downhill ski slopes and areas from around the globe powered by the underlying OpenSkiMap/OpenStreetMap data. The first application is the creation of roses showing the compass orientations of ski areas.
The analyze workflow performs a complete installation of dependencies on Linux and runs the analysis.
It serves as the reference for installing dependencies and executing the analysis, as well as the sole deployment route.
For convenience, we provide some local development instructions below.
Installation and execution requires several system dependencies, whose installation and presence varies by platform. The following commands are one method of installation on macOS:
brew install imagemagick@6
# install the fallback font if you don't have it
# otherwise uv run openskistats visualize will warn:
# WARNING:matplotlib.font_manager:findfont: Font family 'Noto Sans CJK JP' not found.
brew install --cask font-noto-sans-cjkFor initial Python setup, first install uv. Then run the following commands:
# install the uv environment in uv.lock
uv sync --extra=dev
# install the pre-commit git hooks
pre-commit installInstall quarto and extensions:
# install quarto story extension
(cd website/story && quarto add --no-prompt https://github.com/qmd-lab/closeread/archive/e3645070dd668004056ae508d2d25d05baca5ad1.zip)Install R and the renv environment:
# Check that R is installed by running:
R --version
# Install the R environment by restoring the project's dependencies in the `renv.lock` file:
Rscript -e "setwd('r'); renv::restore()"For commands that require access to the python environment,
which includes those beginning with openskistats and quarto,
you can activate the uv environment any of the following ways:
- configure your IDE to activate the venv automatically, e.g. via "Python: Select Interpreter" in Visual Studio Code.
- prefix the command with
uv run, e.g.uv run openskistats --help - activate the venv like
source .venv/bin/activate
To execute the Python analysis, run the following commands:
# download latest OpenSkiMap data
# run infrequently as we want to minimize stress on the OpenSkiMap servers
# downloads persist locally
openskistats download
# extract ski area metadata and metrics
openskistats analyze
openskistats visualize
# run python test suite
pytest
# run the full pre-commit suite
pre-commit run --allTo execute the R analysis, run the following command:
cd r
Rscript 01.data.R
Rscript 02.plot.RTo render the website, use either:
# using quarto preview to render and serve
quarto preview website
# render and serve to <http://localhost:8000> manually
quarto render website
python -m http.server --directory=data/webappList of related webpages not yet mentioned in the manuscript:
- https://avalanche.org/avalanche-encyclopedia/terrain/slope-characteristics/aspect/
- https://www.onxmaps.com/backcountry/app/features/slope-aspect-map
- https://en.wikipedia.org/wiki/Aspect_(geography)
- https://gisgeography.com/aspect-map/
- https://www.nsaa.org/NSAA/Media/Industry_Stats.aspx
- https://www.skitalk.com/threads/comparing-latitude-and-elevation-at-western-us-resorts.9980/
- https://gitlab.com/hugfr/european-ski-resorts-snow-reliability and https://zenodo.org/records/8047168
- https://mapsynergy.com/ and https://mapsynergy.maps.arcgis.com/apps/dashboards/44d9c8422f3c4cc898642d75392337db
- https://snowbrains.com/inconsistencies-in-classification-of-ski-slope-difficulty-ratings/
- https://steepseeker.com/
- Closeread Prize Submission: Which way do you ski?
- https://www.reddit.com/r/skiing/comments/1i03r3c/which_way_do_you_ski_introducing_openskistats/
- Table of all OpenStreetMap users that have contributed to ski areas, i.e. top skiers
- Max slope v difficulty by region
- fix matplotlib super title spacing
- openskimap.org/issues/82: Add slope aspect information
- openskimap.org/issues/135: ski_areas.geojson location information is missing
- openskimap.org/issues/137: Restrict coordinate precision to prevent floating-point rounding errors
- openskimap.org/issues/141: Extreme negative elevation values in some run coordinates
- openskimap.org/issues/143 Data downloads block access from GitHub Issues
- photon/issues/838 and openskimap.org/issues/139: Black Mountain of New Hampshire USA is missing location region metadata
- osmnx/issues/1137 and osmnx/pull/1139: Support directed bearing/orientation distributions and plots
- osmnx/issues/1143 and osmnx/pull/1147: _bearings_distribution: defer weighting to np.histogram
- osmnx/pull/1149: _bearings_distribution: bin_centers terminology
- patito/issues/103: Validation fails on an empty list
- patito/issues/104: Optional list field with nested model fails to validate
- polars/issues/19771: A no-op filter errors when the dataframe has an all null column
- polars/issues/15322: skip_nulls does not work in map_elements
- reactable-py/issues/25: Column default sort order does not override global default
- reactable-py/issues/28: Column class_ argument only sets the dev class for the first row
- reactable-py/issues/29: Should great_tables be a dependency (currently dev dependency)
- reactable-py/issues/38: How to call custom javascript after the table is loaded?
- quarto-cli/issues/11656: YAML bibliographies should accept list format, currently requires a dictionary with references
- pandoc/issues/10452: YAML bibliographies require an object with references and do not accept arrays
- quarto-cli/discussions/11668: markdown visual editor sentence wrap in figure captions
The code in this repository is released under a BSD-2-Clause Plus Patent License.
This project is built on data from OpenSkiMap, which is based on OpenStreetMap. OpenStreetMap and OpenSkiMap data are released under the Open Data Commons Open Database License. Learn more at https://www.openstreetmap.org/copyright.