ExtremeEarth meets satellite data from space

Desta Haileselassie Hagos, Theofilos Kakantousis, Vladimir Vlassov, Sina Sheikholeslami, Tianze Wang, Jim Dowling, C. Paris, Daniele Marinelli, Giulio Weikmann, Lorenzo Bruzzone, Salman Khaleghian, Thomas Krmer, Torbjorn Eltoft, Andrea Marinoni, Despina-Athanasia Pantazi, Georgios Stamoulis, Dimitris Bilidas, George Papadakis, George Mandilaras, Manolis KoubarakisAntonis Troumpoukis, Stasinos Konstantopoulos, Markus Muerth, Florian Appel, Andrew H Fleming, Andreas Cziferszky

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Bringing together a number of cutting-edge technologies that range from storing extremely large volumes of data all the way to developing scalable machine learning and deep learning algorithms in a distributed manner and having them operate over the same infrastructure poses unprecedented challenges. One of these challenges is the integration of European Space Agency (ESA)'s Thematic Exploitation Platforms (TEPs) and data information access service platforms with a data platform, namely Hopsworks, which enables scalable data processing, machine learning, and deep learning on Copernicus data, and development of very large training datasets for deep learning architectures targeting the classification of Sentinel images. In this article, we present the software architecture of ExtremeEarth that aims at the development of scalable deep learning and geospatial analytics techniques for processing and analyzing petabytes of Copernicus data. The ExtremeEarth software infrastructure seamlessly integrates existing and novel software platforms and tools for storing, accessing, processing, analyzing, and visualizing large amounts of Copernicus data. New techniques in the areas of remote sensing and artificial intelligence with an emphasis on deep learning are developed. These techniques and corresponding software presented in this article are to be integrated with and used in two ESA TEPs, namely Polar and Food Security TEPs. Furthermore, we present the integration of Hopsworks with the Polar and Food Security use cases and the flow of events for the products offered through the TEPs.

Original languageEnglish
Pages (from-to)9038-9063
Number of pages26
JournalIEEE Journal of selected topics in applied earth observations and remote sensing
Volume14
DOIs
Publication statusPublished - 26 Aug 2021
Externally publishedYes

Keywords

  • ITC-CV

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