computationalgeography / land_surface_data_generator

High resolution land surface data with a global coverage is a key requirement as input to global simulation models of, for instance, water resources, air pollution, and land use change. Processing, reproducing and sharing inputs and derived products is a reoccurring challenge due to the amount of intermediate and final data, often implied by a hyper-resolution modelling requirement.

This Python based processing workflow provides a straightforward creation of input data for raster-based global simulation models.

A few steps are required to run the scripts:

1. You will need a working Python environment. We recommend to install Miniconda, or use Anaconda if you have installed that already. Follow the Miniconda instructions given at https://docs.conda.io/en/latest/miniconda.html. The user guide and short reference on Conda can be found here.

2. Open a terminal (Linux/macOS) or Miniconda command prompt (Windows) and browse to a location where you want to store the repository contents.

3. Clone this repository, or download and uncompress the zip file. Afterwards change to the land_surface_data_generator folder.

4. Create the required Python environment:

   Linux/macOS:

   conda env create -f environment/environment.yaml

   Windows:

   conda env create -f environment\course_environment.yaml

The environment file will create a environment named lsdg using a recent Python version. In case you prefer a different name or Python version you need to edit the environment file.