This is a collection of example notebooks showcasting the capabilities of E:earth_africa:dal (Earth Observation Data Analysis Library).

The notebook "Sentinel-2 crop growing conditions" is the fully-reproducible example highlighted in

Graf, L.V, et al. (2022): EOdal: An Open-Source Python Package for Large Scale Agricultural Research Using Earth Observation and Gridded Environmental Data. Computers & Electronics in Agriculture, 203. https://doi.org/10.1016/j.compag.2022.107487

using the open-access Sentinel-2 collection on Microsoft Planetary Computer (no authentication required).

Further resources are available showing the general capacities of E:earth_africa:dal and further Sentinel-2 data handling in a fully reproducible manner.

• General

  • Load Images
  • Introduction to the Mapper class

• Sentinel-2

  • Data Handling
  • Crop Growing Conditions
  • Field Parcel Extraction
  • Zonal Statistics of Field Parcels
  • Sentinel-2 Long Time Series Data to 4-D Numpy Array
  • Green Leaf Area Index Retrieval from Sentinel-2 Imagery

E:earth_africa:dal can be installed from PyPI

pip install eodal

or get the latest source code version from Github by running

pip install git+https://github.com/EOA-team/eodal

Furthermore, a step-by-step guide shows you how to run the notebooks in a Docker container that can be found below.

Install Docker on your machine. An installation guide to get Docker running on your system can be found here. We strongly recommend to use Docker to run the notebooks in a JupyterLab environment to avoid any dependency problems (especially with rasterio).

Once the docker daemon is running (on linux systems by running, e.g., sudo service docker start) build the container first using

docker-compose build

and start the service then by

docker-compose up -d

Finally, open your browser and go to (0.0.0.0:8888 or localhost:8888) to access the Jupyter server login page. The token is docker.

Now, you can re-run all Notebooks.

See the license file.

E:earth_africa:dal and E:earth_africa:dal_notebooks are actively maintained by a team of researchers and Python enthusiasts at the Earth Observation of Agroecosystems Team at the Swiss centre of excellence for agricultural research (Agroscope) and the Group of Crop Science at ETH Zurich.

See authors.txt for a full list of current and past developers who contributed to this repository.

Contributions (reporting bugs, fixing bugs, development of new features, writing and improving tests and documentation, etc.) are welcome. Please always open an Issue in the issue-board first.