These general tutorials are meant to concisely demonstrate how to apply numerical and GIS python to analyze SAR and other remotely sensed data for basic environmental monitoring and land use classification. We have some simple functions which we include under rscube, though they are basic wrappers around the powerful GIS libraries rasterio, geopandas, etc.

1. Download the repository.

2. Open the terminal.

3. Change the working directory of the terminal session to the downloaded repository.

4. Create a virtual environment using conda via:

   conda create --name rscube python=3.7 --yes

   Make sure to hit y to confirm that the listed packages can be downloaded for this environment.

5. Activate the virtual environment:

   conda activate rscube.

6. Install requirements with pip:

   pip install -r requirements.txt

   or with conda:

   conda install -c conda-forge --yes --file requirements.txt

7. Install rscube into the environment:

   pip install .

8. Create a new jupyter kernel:

   python -m ipykernel install --user --name rscube.

See LICENSE.txt.

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