Articles | Volume 17, issue 11
https://doi.org/10.5194/tc-17-4957-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-4957-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Nov 2023
Research article |
| 24 Nov 2023
| 24 Nov 2023
Out-of-the-box calving-front detection method using deep learning
Institute of Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Nora Gourmelon
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Thorsten Seehaus
Institute of Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Andreas Maier
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Johannes J. Fürst
Institute of Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Matthias H. Braun
Institute of Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Vincent Christlein
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Ice loss of glaciers shows in retreating calving fronts (i.e., the position where icebergs break off the glacier and drift into the ocean). This paper presents a benchmark dataset for calving front delineation in synthetic aperture radar (SAR) images. The dataset can be used to train and test deep learning techniques, which automate the monitoring of the calving front. Provided example models achieve front delineations with an average distance of 887 m to the correct calving front.
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Arctic glaciers have been subject to extensive warming due to global climate change, yet their contribution to sea level rise has been relatively small in the past. In this study we provide mass changes of most glaciers of the Russian High Arctic (Franz Josef Land, Severnaya Zemlya, Novaya Zemlya). We use TanDEM-X satellite measurements to derive glacier surface elevation changes. Our results show an increase in glacier mass loss and a sea level rise contribution of 0.06 mm/a (2010–2017).
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Earth Syst. Sci. Data, 13, 4653–4675, https://doi.org/10.5194/essd-13-4653-2021, https://doi.org/10.5194/essd-13-4653-2021, 2021
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Consistent and continuous data on glacier surface velocity are important inputs to time series analyses, numerical ice dynamic modeling and glacier mass flux computations. We present a new data set of glacier surface velocities derived from Sentinel-1 radar satellite data that covers 12 major glaciated regions outside the polar ice sheets. The data comprise continuously updated scene-pair velocity fields, as well as monthly and annually averaged velocity mosaics at 200 m spatial resolution.
Mirko Scheinert, Christoph Mayer, Martin Horwath, Matthias Braun, Anja Wendt, and Daniel Steinhage
Polarforschung, 89, 57–64, https://doi.org/10.5194/polf-89-57-2021, https://doi.org/10.5194/polf-89-57-2021, 2021
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Ice sheets, glaciers and further ice-covered areas with their changes as well as interactions with the solid Earth and the ocean are subject of intensive research, especially against the backdrop of global climate change. The resulting questions are of concern to scientists from various disciplines such as geodesy, glaciology, physical geography and geophysics. Thus, the working group "Polar Geodesy and Glaciology", founded in 2013, offers a forum for discussion and stimulating exchange.
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Short summary
Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Delineating calving fronts of marine-terminating glaciers in satellite images is a...
