Recognizing the Shape and Size of Tundra Lakes in Synthetic Aperture Radar (SAR) Images Using Deep Learning Segmentation

• Published in: Remote Sensing
• Main Authors: Demchev, Denis, Sudakow, Ivan, Khodos, Alexander, Abramova, Irina, Lyakhov, Dmitry, Michels, Dominik L.
• Other Authors: Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computer Science Program, Visual Computing Center (VCC), Department of Space, Earth and Environment, Chalmers University of Technology, 412 96 Gothenburg, Sweden, School of Mathematics and Statistics, The Open University, Milton Keynes MK7 6AA, UK, The Center for Research and Invention, Veliky Novgorod 173008, Russia, Arctic and Antarctic Research Institute, Saint Petersburg 199397, Russia
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: MDPI AG 2023
• Subjects: The Sentinel; Yamal Peninsula; permafrost; Tundra; Alaska
• Online Access: http://hdl.handle.net/10754/689840; https://doi.org/10.3390/rs15051298

Permafrost tundra contains more than twice as much carbon as is currently in the atmosphere, and it is warming six times as fast as the global mean. Tundra lakes dynamics is a robust indicator of global climate processes, and is still not well understood. Satellite data, particularly, from synthetic...