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Professur für Geodätische Erdsystemforschung
Dieser Bereich ist Open Access und öffentlich zugänglich.
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Artificial Intelligence for Cold Regions (AI-CORE) [5]
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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Manually delineated glacier calving front locations of 27 marine-terminating glaciers from 2013 to 2021
(Technische Universität Dresden, 2024)This dataset provides 898 manually delineated glacier calving front positions of 23 Greenland glaciers, two glaciers at the Antarctic Peninsula, one glacier in Svalbard and one glacier in Patagonia from 2013 to 2021. For ... -
Terminus area change of 17 key glaciers of the Antarctic Peninsula from 2013 to 2023 derived from remote sensing and deep learning
(Technische Universität Dresden, 2023)Glacier terminus area changes are derived using the rectilinear box method applied to time series of glacier calving front locations. Terminus changes are provided in text file and image format. The following glaciers are ... -
Historical Greenland glacier calving front locations from 1973 until 2013
(Technische Universität Dresden, 2023)This product contains 170 Greenland glacier calving front positions from the following glaciers: Hagen Bræ, Helheim Glacier, Kangiata Nunaata Sermia, Nioghalvfjerdsbræ, Tracy Glacier and Zachariae Isstrøm. The glacier ... -
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 ...
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