In this repository are a set of Jupyter notebooks that explore UP42. They are examples of the things you can do using UP42. The list of notebooks is continually being expanded to reflect new features, aspects or example applications. Star the repository and check regulary for updates.
- The
config.jsonfile is just a template for you to add your credentials. - Copy
config.jsontomyconfig.jsonand add your credentials. All notebooks expect the credentials to be inmyconfig.json. myconfig.jsonis in.gitignoreso as long you keep this convention there is little chance of you accidentally leaking your credentials when committing to agit repository.
-
sdk_retrieve_data_conditionally.ipynbis a Jupyter notebook that shows how to subscribe for new data being available for a given set of parameters. -
computing_vegetation_indexes_scale.ipynbis a Jupyter notebook that shows how to easily compute the most usual vegetation indexes using gdal_calc. -
ground_displacement_interferometry_catalyst.ipynbis a Jupyter notebook that uses the Catalyst Ground Displacement algorithm based on Synthetic Aperture Radar](https://earthdata.nasa.gov/learn/backgrounders/what-is-sar) (SAR) Interferometry (InSAR) to estimate the ground displacement ahead of the February 7th 2021 Rishi Ganga Valley landslide.
To contribute to this repository please you must abide by the following rules:
- All development happens in the
devbranch. - Never commit notebooks with output to the
devbranch. - Commit notebooks with output only to the
masterbranch. - When you are happy with the resulting notebook, before committing
to
masterdo the following:- Clear All Outputs.
- Run All Cells.
- After, and only after, veryfing that all output is correct commit to master.
- Done.
This procedure, as described
here, makes sure we
minimize the commits of changed output and gives you always a clean
(no output) version of each notebook in the dev branch.
- Add other examples on using the UP42 API.
Either create an issue here or send an email to [email protected].