Professur für Geodätische Erdsystemforschung
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Artificial Intelligence for Cold Regions (AI-CORE) In “Artificial Intelligence for Cold Regions” (AI-CORE) we will develop a collaborative approach for applying Artificial Intelligence (AI) methods in earth observation and thereby breaking new ground for researching the ...
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Data product of Greenland glacier calving front locations delineated by deep learning, 2013 to 2021 (Technische Universität Dresden, 2023)Glacier calving front positions are derived by applying a deep learning method to multispectral Landsat-8 imagery. The product contains 9243 calving front positions across 23 Greenland outlet glaciers from March 2013 to ...
Sensitivity kernels for four different methods of Greenland Ice Sheet mass change estimation from GRACE Level-2 satellite gravimetry data (Technische Universität Dresden, 2023)Supplementary material to the manuscript: Döhne, T., Horwath, M., Groh, A. and Buchta, E. (2023) 'The sensitivity kernel perspective on GRACE mass change estimates', Journal of Geodesy. The data set comprises sensitivity ...
Manually delineated glacier calving fronts of 23 Greenland and 2 Antarctic outlet glaciers from 2013 to 2021 and source code for automated extraction by deep learning (Technische Universität Dresden, 2022)Supplementary material to the manuscript: Loebel, E., Scheinert, M., Horwath, M., Heidler, K., Christmann, J., Phan, L., Humbert, A., Zhu, X. (2022): Extracting glacier calving fronts by deep learning: the benefit of ...