Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery
Extents of Antarctica`s ice shelves and ice streams are sensitive indicators of glaciological and environmental change. Retreat of glacier fronts and break ups of ice shelves have been linked to oceanic and atmospheric warming. Weakening or disintegration of ice shelfs reduces buttressing of their t...
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ftdlr:oai:elib.dlr.de:127197 2024-05-19T07:29:51+00:00 Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery Baumhoer, Celia Dietz, Andreas Kuenzer, Claudia 2019-04-11 https://elib.dlr.de/127197/ unknown Baumhoer, Celia und Dietz, Andreas und Kuenzer, Claudia (2019) Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery. EGU 2019, 2019-04-07 - 2019-04-12, Wien. Dynamik der Landoberfläche Konferenzbeitrag NonPeerReviewed 2019 ftdlr 2024-04-25T00:50:07Z Extents of Antarctica`s ice shelves and ice streams are sensitive indicators of glaciological and environmental change. Retreat of glacier fronts and break ups of ice shelves have been linked to oceanic and atmospheric warming. Weakening or disintegration of ice shelfs reduces buttressing of their tributary glaciers, leading to ice flow acceleration and increased sea level rise contribution. Hence, monitoring changes in ice extent is of keen interest. So far, ice fronts have mostly been delineated by manual extraction. However, this time consuming approach does no longer allow coping with the abundance of modern satellite imagery. For example, Sentinel-1 provides year-round cloudless data with weekly revisit times. Therefore, it is necessary to fully automatize ice shelf front extraction. We propose a new approach to extract calving fronts from Sentinel-1 imagery with a combination of image processing techniques. First, the deep learning architecture U-Net is used to perform a semantic segmentation on the satellite imagery. Each pixel is assigned to a probability for being either water or ice based on backscatter as well as contextual and spatial information. Second, an active contour model delineates a continuous front based on the output of the U-Net. For different test sites satisfying results are obtained. Nevertheless, still some improvements of the algorithm are necessary for example in regions where glacier margins are enclosed by ice mélange. The future implementation of the developed algorithm for Sentinel-1 imagery will provide a valuable source to monitor fluctuations in Antarctic ice shelf and glacier front locations. Conference Object Antarc* Antarctic Antarctica Ice Shelf Ice Shelves German Aerospace Center: elib - DLR electronic library |
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Open Polar |
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German Aerospace Center: elib - DLR electronic library |
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Dynamik der Landoberfläche |
spellingShingle |
Dynamik der Landoberfläche Baumhoer, Celia Dietz, Andreas Kuenzer, Claudia Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
topic_facet |
Dynamik der Landoberfläche |
description |
Extents of Antarctica`s ice shelves and ice streams are sensitive indicators of glaciological and environmental change. Retreat of glacier fronts and break ups of ice shelves have been linked to oceanic and atmospheric warming. Weakening or disintegration of ice shelfs reduces buttressing of their tributary glaciers, leading to ice flow acceleration and increased sea level rise contribution. Hence, monitoring changes in ice extent is of keen interest. So far, ice fronts have mostly been delineated by manual extraction. However, this time consuming approach does no longer allow coping with the abundance of modern satellite imagery. For example, Sentinel-1 provides year-round cloudless data with weekly revisit times. Therefore, it is necessary to fully automatize ice shelf front extraction. We propose a new approach to extract calving fronts from Sentinel-1 imagery with a combination of image processing techniques. First, the deep learning architecture U-Net is used to perform a semantic segmentation on the satellite imagery. Each pixel is assigned to a probability for being either water or ice based on backscatter as well as contextual and spatial information. Second, an active contour model delineates a continuous front based on the output of the U-Net. For different test sites satisfying results are obtained. Nevertheless, still some improvements of the algorithm are necessary for example in regions where glacier margins are enclosed by ice mélange. The future implementation of the developed algorithm for Sentinel-1 imagery will provide a valuable source to monitor fluctuations in Antarctic ice shelf and glacier front locations. |
format |
Conference Object |
author |
Baumhoer, Celia Dietz, Andreas Kuenzer, Claudia |
author_facet |
Baumhoer, Celia Dietz, Andreas Kuenzer, Claudia |
author_sort |
Baumhoer, Celia |
title |
Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
title_short |
Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
title_full |
Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
title_fullStr |
Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
title_full_unstemmed |
Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery |
title_sort |
towards an automatic delineation of antarctic glacier and ice shelf fronts from sentinel-1 imagery |
publishDate |
2019 |
url |
https://elib.dlr.de/127197/ |
genre |
Antarc* Antarctic Antarctica Ice Shelf Ice Shelves |
genre_facet |
Antarc* Antarctic Antarctica Ice Shelf Ice Shelves |
op_relation |
Baumhoer, Celia und Dietz, Andreas und Kuenzer, Claudia (2019) Towards an automatic delineation of Antarctic glacier and ice shelf fronts from Sentinel-1 imagery. EGU 2019, 2019-04-07 - 2019-04-12, Wien. |
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1799481880520687616 |