Guidance for avoiding common pitfalls when producing and using datacubes.

Status: This is a first draft of the guidance.

Installation

git clone https://github.com/developmentseed/datacube-guide.git
cd datacube-guide
# Serve the documentation
uv run -- mkdocs serve
# Try out the `datacube_benchmark` library in Python
uv run python
# Try out the `datacube_benchmark` library in JupyterLab
uv run ipython kernel install --user --env VIRTUAL_ENV $(pwd)/.venv --name=project
uv run --with jupyter jupyter lab

Acknowledgements

The Datacube Guide was initiated in partnership with the Microsoft Planetary Computer team. We recommend checking out the wonderful work going on as part of the Microsoft Planetary Computer Pro service as well as the Open Planetary Computer Data Catalog. We greatly appreciate Microsoft's dedication to supporting open resources and building impactful geospatial services.

License

datacube-guide is distributed under the terms of the MIT license.