Repository for Digital Earth Africa Sandbox, including: Jupyter notebooks, scripts, tools and workflows for geospatial analysis with Open Data Cube and xarray
# Digital Earth Africa Notebooks
**License:** The code in this repository is licensed under the Apache License, Version 2.0. Digital Earth Africa data is licensed under the Creative Commons by Attribution 4.0 license.
**Contact:** If you need assistance with any of the Jupyter Notebooks or Python code in this repository, please post a question on the Open Data Cube Slack channel or on the GIS Stack Exchange using the `open-data-cube` tag (you can view `previously asked questions` here. If you would like to report an issue with any of the scripts or notebooks in this repository, you can file one on the Github issues page.
**Citing DE Africa Notebooks:** If you use any of the notebooks, code or tools in this repository in your work, please reference them using the following citation:
Burton, C., Neema, V., Boamah, E., Chong, E., Adams, C., Wellington, M., Sadiki, M., Moghaddam, N., Liu, L., Bishop-Taylor, R., Yuan, F., Leith, A., Jorand, C., Halabisky, M., Rebelo, L-M, DE Africa Notebooks contributors 2024. Digital Earth Africa notebooks and tools repository. Geoscience Australia, Canberra.
dx.doi.org
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The Digital Earth Africa Notebooks repository (`deafrica-sandbox-notebooks`) hosts Jupyter Notebooks, Python scripts and workflows for analysing Digital Earth Africa (DE Africa) satellite data and derived products. This documentation is designed to provide a guide to getting started with DE Africa, and to showcase the wide range of geospatial analyses that can be achieved using DE Africa data and open-source software including Open Data Cube and xarray.
The repository is based around the following directory structure (from simple to increasingly complex applications):
1. Beginners_guide: *Introductory notebooks aimed at introducing Jupyter Notebooks and how to load, plot and interact with DE Africa data.*
2. Datasets: *Notebooks introducing DE Africa's satellite datasets and derived products, including how to load each dataset and a …