Artificial Intelligence and Big Data Technologies for Copernicus Data: The ExtremeEarth Project

• Main Authors: Koubarakis, Manolis, Pantazi, Despina-Athanasia, Stamoulis, George, Vlassov, Vladimir, Bruzzone, Lorenzo, Paris, Claudia, Eltoft, Torbjørn, Marinoni, Andrea, Kraemer, Thomas, Dowling, Jim, Kakantousis, Theofilos, Datcu, Mihai, Yao, Wei, Dumitru, Corneliu Octavian, Appel, Florian, Migdall, Silke, Muerth, Markus, Hughes, Nick, Everett, Alistar, Arthurs, David, Fleming, Andrew, Kiærbech, Ashild, Pedersen, Joakim Lillehaug, Cziferszky, Andreas, Haileselassie Hagos, Desta, Sheikholeslami, Sina, Ioannidis, Theofilos, Bilidas, Dimitris, Bach, Heike
• Format: Conference Object
• Language: unknown
• Published: JRC 2021
• Subjects: EO Data Science; Sea ice
• Online Access: https://elib.dlr.de/144998/; https://www.bigdatafromspace2021.org/

ExtremeEarth is a three-year H2020 ICT research and innovation project which is currently in its final year. The main objective of ExtremeEarth is to develop Artificial Intelligence and Big Data techniques and technologies that scale to the large volumes of big Copernicus data, information and knowledge, and apply these technologies in two of the ESA Thematic Exploitation Platforms: Food Security and Polar. The technical contributions of the project so far include: (i) new deep learning architectures for crop type mapping in the context of the Food Security use case, (ii) new deep learning architectures for sea ice mapping in the context of the Polar use case, (iii) the development and open publication of very large datasets for training these architectures, (iv) new versions of scalable semantic technologies for managing big linked geospatial data, and (v) a new platform for bringing all the previous technologies together and applying them to the two use cases.