EO AFRICA Online Course: Cloud Computing and algorithms for EO analyses

This course introduces participants to Cloud Computing and its usage for Earth Observation (EO) data analyses. It starts with big geospatial data concepts and extends to Cloud Computing as one of the solutions for solving the problems of big EO data.

The EOAFRICA Facility Innovation Lab will be introduced as an example of a cloud computing platform for working with EO data. We will cover Jupyter Notebooks and JupyterLab as the proper solution for developing analytical procedures accompanied with documentation on cloud computing platforms.

The course focuses on some of the Python libraries to develop programs that handle and analyze EO data. We will explain how participants can programmatically access different EO datasets using online catalogue services and utilize the data in their algorithms. Particularly, we explain the key features and recent developments of openEO platform for EO data analyses.

Participants apply the knowledge and skills gained on a final project using EO data available on the Innovation Lab.

This course will provide participants with:

• An understanding of Cloud Computing and its benefits for EO (Earth Observation) analysis.
• A comparison of various cloud computing platforms.
• Hands-on experience with the Innovation Lab, the cloud computing platform offered by the EO AFRICA R&D Facility.
• Hands-on experience with key Python libraries for EO data processing.
• The ability to implement processing workflows through interactive Jupyter Notebooks on the Innovation Lab.
• Knowledge on how to load and process EO data from DIAS platforms.
• The capability to load and process EO data using Python libraries.
• Hands-on experience in implementing Python-based workflows on openEO platform.

Only applicants working for an African-based organization are eligible.

Application Deadline: November 1, 2024