Cloud Computing and algorithms for EO analyses

1st EO AFRICA R&D Facility Online Course

Cloud Computing and algorithms for EO analyses

Introduction to the course

This course introduces participants to Cloud Computing and its usage for Earth Observation (EO) data analysis. 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 EO AFRICA 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.

In the next step, 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 catalog services and utilize the data in their algorithms.

Participants apply the knowledge and skills gained on a final project using EO data available on the Innovation Lab. Materials will be made available through a dedicated Moodle site.

Prerequisites

The participants need to have basic programming skills in Python.

Selection

The course will be offered to a maximum of 65 participants. Selection will be based on relevant academic background and employment. We will strive to have a gender-balanced and country-balanced group of participants. Preference is given to candidates working as (Ph.D.-) researchers, post-doc, and university staff.

Timeline:

The online course will have sessions on:

  • March 16
  • March 17
  • March 23
  • March 24
  • March 30
  • March 31
  • April 1

Registration:

Speakers: