This repository contains openEO workflows for various python modules used in Evapotranspiration (ET) modeling and Irrigation mapping.
Following modules are currently included:
- first install GDAL on your machine
- Then install the package from Github
pip install eomaji@git+https://github.com/DHI/EOMAJI-OpenEO-toolbox.git
The notebooks provided in the notebooks/
folder demonstrate how to use the EOMAJI OpenEO toolbox for evapotranspiration modeling.
These notebooks can be run directly on Copernicus Data Space (CDSE) JupyterHub for efficient processing and scalability.
-
notebooks/pydms_example.ipynb
– Demonstrates how to use the Data Mining Sharpener (pyDMS) to refine Sentinel-3 Land Surface Temperature (LST) using Sentinel-2 reflectance data. -
notebooks/et_input_parameters.ipynb
– Focuses on downloading and preprocessing meteorological and biophysical input data. This includes:- Retrieving meteorological parameters from the Copernicus Climate Data Store (CDS).
- Extracting vegetation indices and land cover parameters from Sentinel-2 and ESA WorldCover datasets.
-
notebooks/et_tseb.ipynb
– Runs the Two Source Energy Balance (TSEB) model to estimate evapotranspiration. It takes as input:- Sharpened LST from pyDMS.
- Preprocessed meteorological and vegetation parameters.
These notebooks form a complete workflow, from data retrieval and preprocessing to sharpening LST and running the ET model.
For development, you can set up the environment in one of two ways:
-
Using a Dev Container This repository includes a devcontainer setup, which provides a pre-configured environment for development.
-
Manual Setup If you prefer a local setup
- Install GDAL
- Create a virtual environment and install the package:
python -m venv eomaji-env source eomaji-env/bin/activate # On Windows, use `eomaji-env\Scripts\activate` pip install .