The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-4/W12-2024
https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-157-2024
https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-157-2024
20 Jun 2024
 | 20 Jun 2024

MOOC Cubes and Clouds - Cloud Native Open Data Sciences for Earth Observation

Peter James Zellner, Michele Claus, Tyna Dolezalova, Rufai Omowunmi Balogun, Jonas Eberle, Henryk Hodam, Robert Eckardt, Stephan Meißl, Alexander Jacob, and Anca Anghelea

Keywords: MOOC, education, open science, data cubes, cloud platforms

Abstract. The "Cubes and Clouds" Massive Open Online Course (MOOC) addresses the growing challenges and opportunities in Earth Observation (EO) data analysis posed by the exponential growth of satellite missions and data volumes. This course introduces cloud-native EO concepts and open science principles, facilitating collaboration and data sharing within the EO community.
Key topics covered in the MOOC include data discovery, processing workflows, and data sharing using real-world examples like snow cover mapping in the Alps. Participants engage with interactive lessons, videos, and hands-on coding exercises, leveraging freely available geospatial data and emphasizing open data principles and interoperability.
The course infrastructure seamlessly integrates with cloud platforms like the Copernicus Data Space Ecosystem, enabling learners to apply concepts in a practical, cloud-based environment. Initial user statistics indicate strong interest, particularly among early-career professionals and researchers, with participant surveys suggesting increased confidence in using EO cloud platforms and embracing open science practices upon course completion.
Overall, "Cubes and Clouds" serves as a valuable resource for the EO community, fostering transparency, collaboration, and innovation in geospatial science. Future developments aim to expand course content and attract diverse user groups, ensuring broader accessibility and long-term impact in advancing cloud-native EO and open science initiatives.