DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING

Change detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely v...

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Main Authors: J. Zhao, M. Chini, R. Pelich, P. Matgen, R. Hostache, S. Cao, W. Wagner
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-1-2020/395/2020/isprs-annals-V-1-2020-395-2020.pdf
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author J. Zhao
J. Zhao
M. Chini
R. Pelich
P. Matgen
R. Hostache
S. Cao
W. Wagner
author_facet J. Zhao
J. Zhao
M. Chini
R. Pelich
P. Matgen
R. Hostache
S. Cao
W. Wagner
author_sort J. Zhao
collection DOAJ
description Change detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely vegetated areas, where the SAR backscatter is not sufficiently impacted by floodwater-related surface changes. This study focuses on these so-called exclusion areas, i.e. areas where SAR does not allow detecting water based on change detection. Our approach considers both pixel-based time series analyses and object-based spatial analyses using 20m Sentinel-1 Interferometric Wide Swath data, including 922 Sentinel-1 tiles covering the River Severn basin (UK) and the Lake Maggiore area (Italy). The results show that our exclusion map presents a good agreement (∼63%) with reference data derived from different data sources and indicate that it may complement SAR-derived flood extent maps. Allowing to accurately identify potential misclassifications in flood extent mapping, our exclusion map provides valuable information for flood management and, in particular, flood forecasting and prediction.
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spelling doaj.art-2bafda8a8c084be8bb641d3c9f3f51c42022-12-22T00:17:31ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502020-08-01V-1-202039540010.5194/isprs-annals-V-1-2020-395-2020DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPINGJ. Zhao0J. Zhao1M. Chini2R. Pelich3P. Matgen4R. Hostache5S. Cao6W. Wagner7Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, LuxembourgResearch Group Remote Sensing, Department of Geodesy and Geoinformation, Vienna University of Technology, AustriaDepartment of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, LuxembourgDepartment of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, LuxembourgDepartment of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, LuxembourgDepartment of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, LuxembourgResearch Group Remote Sensing, Department of Geodesy and Geoinformation, Vienna University of Technology, AustriaResearch Group Remote Sensing, Department of Geodesy and Geoinformation, Vienna University of Technology, AustriaChange detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely vegetated areas, where the SAR backscatter is not sufficiently impacted by floodwater-related surface changes. This study focuses on these so-called exclusion areas, i.e. areas where SAR does not allow detecting water based on change detection. Our approach considers both pixel-based time series analyses and object-based spatial analyses using 20m Sentinel-1 Interferometric Wide Swath data, including 922 Sentinel-1 tiles covering the River Severn basin (UK) and the Lake Maggiore area (Italy). The results show that our exclusion map presents a good agreement (∼63%) with reference data derived from different data sources and indicate that it may complement SAR-derived flood extent maps. Allowing to accurately identify potential misclassifications in flood extent mapping, our exclusion map provides valuable information for flood management and, in particular, flood forecasting and prediction.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-1-2020/395/2020/isprs-annals-V-1-2020-395-2020.pdf
spellingShingle J. Zhao
J. Zhao
M. Chini
R. Pelich
P. Matgen
R. Hostache
S. Cao
W. Wagner
DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
title_full DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
title_fullStr DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
title_full_unstemmed DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
title_short DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING
title_sort deriving exclusion maps from c band sar time series an additional information layer for sar based flood extent mapping
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-1-2020/395/2020/isprs-annals-V-1-2020-395-2020.pdf
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