Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery

This paper presents an approach for automatic calving front delineation of marine-terminating outlet glaciers. We utilize a Canny edge detection approach together with a shortest path optimization problem to find calving front locations (CFL) on SAR backscattering images from Sentinel-1 and TerraSAR...

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Bibliographic Details
Main Authors: Krieger, Lukas, Floricioiu, Dana
Format: Conference Object
Language:English
Published: 2017
Subjects:
SAR-Signalverarbeitung
Greenland
Online Access:https://elib.dlr.de/114563/
https://elib.dlr.de/114563/1/2017_IGARSS_abstract.pdf
id ftdlr:oai:elib.dlr.de:114563
record_format openpolar
spelling ftdlr:oai:elib.dlr.de:114563 2024-05-19T07:41:15+00:00 Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery Krieger, Lukas Floricioiu, Dana 2017 application/pdf https://elib.dlr.de/114563/ https://elib.dlr.de/114563/1/2017_IGARSS_abstract.pdf en eng https://elib.dlr.de/114563/1/2017_IGARSS_abstract.pdf Krieger, Lukas und Floricioiu, Dana (2017) Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017-07-23 - 2017-07-28, Fort Worth, Texas, USA. SAR-Signalverarbeitung Konferenzbeitrag NonPeerReviewed 2017 ftdlr 2024-04-25T00:42:56Z This paper presents an approach for automatic calving front delineation of marine-terminating outlet glaciers. We utilize a Canny edge detection approach together with a shortest path optimization problem to find calving front locations (CFL) on SAR backscattering images from Sentinel-1 and TerraSARX. The CFLs are detected on Stripmap images acquired over Zachariae Isstroem in Northeast Greenland where difficult conditions for CFL retrieval exist. We compare our results to CFLs that are delineated by hand and find good agreement, independent of the used sensor. Conference Object Greenland German Aerospace Center: elib - DLR electronic library
institution Open Polar
collection German Aerospace Center: elib - DLR electronic library
op_collection_id ftdlr
language English
topic SAR-Signalverarbeitung
spellingShingle SAR-Signalverarbeitung
Krieger, Lukas
Floricioiu, Dana
Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
topic_facet SAR-Signalverarbeitung
description This paper presents an approach for automatic calving front delineation of marine-terminating outlet glaciers. We utilize a Canny edge detection approach together with a shortest path optimization problem to find calving front locations (CFL) on SAR backscattering images from Sentinel-1 and TerraSARX. The CFLs are detected on Stripmap images acquired over Zachariae Isstroem in Northeast Greenland where difficult conditions for CFL retrieval exist. We compare our results to CFLs that are delineated by hand and find good agreement, independent of the used sensor.
format Conference Object
author Krieger, Lukas
Floricioiu, Dana
author_facet Krieger, Lukas
Floricioiu, Dana
author_sort Krieger, Lukas
title Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
title_short Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
title_full Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
title_fullStr Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
title_full_unstemmed Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery
title_sort automatic calving front delienation on terrasar-x and sentinel-1 sar imagery
publishDate 2017
url https://elib.dlr.de/114563/
https://elib.dlr.de/114563/1/2017_IGARSS_abstract.pdf
genre Greenland
genre_facet Greenland
op_relation https://elib.dlr.de/114563/1/2017_IGARSS_abstract.pdf
Krieger, Lukas und Floricioiu, Dana (2017) Automatic calving front delienation on TerraSAR-X and Sentinel-1 SAR imagery. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017-07-23 - 2017-07-28, Fort Worth, Texas, USA.
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