What is this course about?
Welcome to ‘Cubes & Clouds’.
This course teaches the concepts of data cubes, cloud platforms, and open science in the context of earth observation.
Available in February 2024
Registration will be possible soon. The course goes online in early 2024.
Who is the course for?
It targets Earth Science students and researchers who want to increase their technical capabilities onto the newest standards in EO computing, as well as Data Scientists who want to dive into the world of EO and apply their technical background to a new field.
What will you learn?
The course explains the concepts of data cubes, EO cloud platforms, and open science by applying them to a typical EO workflow from data discovery, and data processing up to sharing the results in an open and FAIR (Findable, Accessible, Interoperable, Reusable) way. An engaging mixture of videos, animated content, lectures, hands-on exercises, and quizzes transmits the content.
You will learn the theoretical concepts of cloud native EO processing and have gained practical experience by conducting an end-to-end EO workflow. You will be capable of independently using cloud platforms to approach EO-related research questions and be confident in how to share research by adhering to the concepts of open science.
As proof of the acquired skills a community snow cover map is created where every participant contributes and shares his results openly and FAIR: Cubes and Clouds: Snow Cover STAC Collection
How is the course structured?
The course is structured into three lessons. Each one builds on the knowledge acquired in the previous lessons. The course will cover the following topics:
- Data Discovery
- Data Processing and Sharing
As soon as you finish the course you can download a diploma supplement here:
Course content is also available on:
How to cite this course:
Zellner, P. J., Dolezalova, T., Claus, M., Balogun, R. O., Eberle, J., Hodam, H., Eckardt, R., Meißl, S., Jacob, A., & Anghelea, A. (2024, January 15). Cubes & Clouds – Cloud Native Open Data Sciences for Earth Observation. Zenodo. https://doi.org/10.5281/zenodo.10513915