The AI-CORE Project - Artificial Intelligence for Cold Regions

• Main Authors: Dietz, Andreas, Baumhoer, Celia, Heidler, Konrad, Mou, LiChao, Nitze, Ingmar, Scheinert, Mirko, Fischer, Georg, Hajnsek, Irena, Christmann, Julia, Roesel, Anja, Loebel, Erik, Long, Duc Phan, Dinter, Tilman, Humbert, Angelika, Grosse, Guido, Zhu, Xiao Xiang
• Format: Conference Object
• Language: unknown
• Published: 2022
• Subjects: Dynamik der Landoberfläche; EO Data Science; Radarkonzepte; Antarc*; Antarctica; Greenland; permafrost
• Online Access: https://elib.dlr.de/187150/; https://meetingorganizer.copernicus.org/EGU22/EGU22-3446.html

Artificial Intelligence for Cold Regions (AI-CORE) is a collaborative approach for applying Artificial Intelligence (AI) methods in the field of remote sensing of the cryosphere. Several research institutes (German Aerospace Center, Alfred-Wegener-Institute, Technical University Dresden) bundled their expertise to jointly develop AI-based solutions for pressing geoscientific questions in cryosphere research. The project addresses four geoscientific use cases such as the change pattern identification of outlet glaciers in Greenland, the object identification in permafrost areas, the detection of calving fronts in Antarctica and the firn-line detection on glaciers. Within this presentation, the four AI-based final approaches for each addressed use case will be presented and exemplary results will be shown. Further on, the implementation of all developed AI-methods in three different computer centers was realized and the lessons learned from implementing several ready-to-use AI-tools in different processing infrastructures will be discussed. Finally, a best-practice example for sharing AI-implementations between different institutes is provided along with opportunities and challenges faced during the present project duration.