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OER on Working with Copernicus Data and OpenEO

--Guide for Teachers--

1. Conceptual Aspects of the Learning Material

This OER module is designed for students and professionals interested in working with Earth Observation (EO) data, particularly data from the Copernicus Program. The module provides background information on the Copernicus Program, the Copernicus Data Space Ecosystem, and EO data processing, as well as a practical exercise using Python and the OpenEO platform.

The tutorial can be used in a variety of learning contexts, including blended learning or independent study. It is especially suited for students of Geoinformatics, Geomatics, or related disciplines. However, it also serves professionals who want to enhance their understanding of spatial data infrastructures (SDIs), EO data, and how to process it.

2. Recommendations for the Use of the Learning Material

2.1 PDF Version

The learning material consists of a PDF file, available in the /docs subfolder. The practical exercise is contained within a Python Jupyter Notebook. Supporting materials include Docker and Docker-Compose files to run the notebook environment. In addition to the PDF, the /src folder contains the source notebooks for exercises.

The PDF can be used digitally or printed and easily integrated into a Learning Management System (LMS). It is unnecessary to upload the entire repository to the LMS, as students will be instructed to clone the GitHub repository themselves to complete the exercises.

2.2 Ways of Using the Learning Material

As a teacher, you should familiarize yourself with both the theoretical background and the practical technologies used in the module. The tutorial is designed to be interactive and hands-on, which will significantly enhance the learning experience.

Recommendations for Teaching:

  • Require students to engage in the practical exercise with the Jupyter Notebooks and Docker environment. This exercise uses real Sentinel-2 data and OpenEO to assess the impact of natural disasters, such as floods. Students will download satellite data and calculate NDVI to inspect vegetation damage.
  • You can expand or adjust the tasks to fit your course or your students' level of experience.

2.3 Re-use, Modification, and Distribution

We encourage you to adapt, re-use, and distribute the material under the open CC-BY-SA 4.0 license. You are also welcome to modify the content to better suit your educational objectives, as long as the original authors and the University of Münster are credited.

We welcome contributions and suggestions. You can submit feedback through the repository’s GitHub issue list.