Welcome to wekeo4land

wekeo4land is a collection of Python- and R-based tools designed to introduce users to the use of land-related data on the WEkEO DIAS (Data Information and Access System) and its JupyterLab environment.

The repository includes hands-on introduction to Copernicus Land Monitoring Service (CLMS) data and demonstrates how to access and analyze it using the Harmonized Data Access (HDA) API, which serves as the core interface to the WEkEO platform.

The material is provided as Jupyter Notebooks, combining code, explanations, and visual outputs to support interactive learning.

The content of this repository is suitable for those completely new to WEkEO, Python, R, Copernicus data and hosted processing environments.

Repository overview

The repository is organized into a set of case studies, each illustrating how Copernicus data can be used for different environmental and land-monitoring applications. The examples are designed to be adaptable and educational, guiding users from data discovery to visualization and analysis. The case studies are:

🌿 land

🤖 ml-grassland-classification

❄️ snow&ice

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How to use this material?

If you are on GitHub/Lab you can visit www.wekeo.copernicus.eu, register for an account and enter the JupyterLab - then follow the instructions below.

If you are currently on the WEkEO JupyterLab you're already in the right place and can start. To clone this repository in to the WEkEO JupyterLab environment open a terminal in the WEkEO JupyterLab, type:

<br> > git clone https://github.com/wekeo/wekeo4land.git<br>

This will create a clone of this repository of notebooks in the working directory on your WEkEO JupyterLab instance.

You can also use this code on your own computer/Jupyter Lab server. To do so, clone the repository and install the required dependencies (Python or R libraries) as listed in each case study.