Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic
The applicability of optical satellite data to quantify coastal erosion across the Arctic is limited due to frequent cloud cover. Synthetic Aperture Radar (SAR) may provide an alternative. The interpretation of SAR data for coastal erosion monitoring in Arctic regions is, however, challenging due to...
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Online Access: | https://doi.org/10.3389/fenvs.2020.00143 https://doaj.org/article/62082c8ecbd842428824536633a06578 |
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fttriple:oai:gotriple.eu:oai:doaj.org/article:62082c8ecbd842428824536633a06578 2023-05-15T14:53:09+02:00 Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic Annett Bartsch Sarah Ley Ingmar Nitze Georg Pointner Gonçalo Vieira 2020-09-01 https://doi.org/10.3389/fenvs.2020.00143 https://doaj.org/article/62082c8ecbd842428824536633a06578 en eng Frontiers Media S.A. 2296-665X doi:10.3389/fenvs.2020.00143 https://doaj.org/article/62082c8ecbd842428824536633a06578 undefined Frontiers in Environmental Science, Vol 8 (2020) Arctic erosion SAR radar coast permafrost geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.3389/fenvs.2020.00143 2023-01-22T19:25:59Z The applicability of optical satellite data to quantify coastal erosion across the Arctic is limited due to frequent cloud cover. Synthetic Aperture Radar (SAR) may provide an alternative. The interpretation of SAR data for coastal erosion monitoring in Arctic regions is, however, challenging due to issues of viewing geometry, ambiguities in scattering behavior and inconsistencies in acquisition strategies. In order to assess SAR applicability, we have investigated data acquired at three different wavelengths (X-, C-, L-band; TerraSAR-X, Sentinel-1, ALOS PALSAR 1/2). In a first step we developed a pre-processing workflow which considers viewing geometry issues (shoreline orientation, incidence angle relationships with respect to different landcover types). We distinguish between areas with foreshortening along cliffs facing the sensor, radar shadow along cliffs facing away and traditional land-water boundary discrimination. Results are compared to retrievals from Landsat trends. Four regions which feature high erosion rates have been selected. All three wavelengths have been investigated for Kay Point (Canadian Beaufort Sea Coast). C- and L-band have been studied at all sites, including also Herschel Island (Canadian Beaufort Sea Coast), Varandai (Barents Sea Coast, Russia), and Bykovsky Peninsula (Laptev Sea coast, Russia). Erosion rates have been derived for a 1-year period (2017–2018) and in case of L-band also over 11 years (2007–2018). Results indicate applicability of all wavelengths, but acquisitions need to be selected with care to deal with potential ambiguities in scattering behavior. Furthermore, incidence angle dependencies need to be considered for discrimination of the land-water boundary in case of L- and C-band. However, L-band has the lowest sensitivity to wave action and relevant future missions are expected to be of value for coastal erosion monitoring. The utilization of trends derived from Landsat is also promising for efficient long-term trend retrieval. The high spatial resolution of ... Article in Journal/Newspaper Arctic Barents Sea Beaufort Sea Herschel Island laptev Laptev Sea permafrost Unknown Arctic Barents Sea Herschel Island ENVELOPE(-139.089,-139.089,69.583,69.583) Kay ENVELOPE(-60.917,-60.917,-64.117,-64.117) Laptev Sea Frontiers in Environmental Science 8 |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
Arctic erosion SAR radar coast permafrost geo envir |
spellingShingle |
Arctic erosion SAR radar coast permafrost geo envir Annett Bartsch Sarah Ley Ingmar Nitze Georg Pointner Gonçalo Vieira Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
topic_facet |
Arctic erosion SAR radar coast permafrost geo envir |
description |
The applicability of optical satellite data to quantify coastal erosion across the Arctic is limited due to frequent cloud cover. Synthetic Aperture Radar (SAR) may provide an alternative. The interpretation of SAR data for coastal erosion monitoring in Arctic regions is, however, challenging due to issues of viewing geometry, ambiguities in scattering behavior and inconsistencies in acquisition strategies. In order to assess SAR applicability, we have investigated data acquired at three different wavelengths (X-, C-, L-band; TerraSAR-X, Sentinel-1, ALOS PALSAR 1/2). In a first step we developed a pre-processing workflow which considers viewing geometry issues (shoreline orientation, incidence angle relationships with respect to different landcover types). We distinguish between areas with foreshortening along cliffs facing the sensor, radar shadow along cliffs facing away and traditional land-water boundary discrimination. Results are compared to retrievals from Landsat trends. Four regions which feature high erosion rates have been selected. All three wavelengths have been investigated for Kay Point (Canadian Beaufort Sea Coast). C- and L-band have been studied at all sites, including also Herschel Island (Canadian Beaufort Sea Coast), Varandai (Barents Sea Coast, Russia), and Bykovsky Peninsula (Laptev Sea coast, Russia). Erosion rates have been derived for a 1-year period (2017–2018) and in case of L-band also over 11 years (2007–2018). Results indicate applicability of all wavelengths, but acquisitions need to be selected with care to deal with potential ambiguities in scattering behavior. Furthermore, incidence angle dependencies need to be considered for discrimination of the land-water boundary in case of L- and C-band. However, L-band has the lowest sensitivity to wave action and relevant future missions are expected to be of value for coastal erosion monitoring. The utilization of trends derived from Landsat is also promising for efficient long-term trend retrieval. The high spatial resolution of ... |
format |
Article in Journal/Newspaper |
author |
Annett Bartsch Sarah Ley Ingmar Nitze Georg Pointner Gonçalo Vieira |
author_facet |
Annett Bartsch Sarah Ley Ingmar Nitze Georg Pointner Gonçalo Vieira |
author_sort |
Annett Bartsch |
title |
Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
title_short |
Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
title_full |
Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
title_fullStr |
Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
title_full_unstemmed |
Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic |
title_sort |
feasibility study for the application of synthetic aperture radar for coastal erosion rate quantification across the arctic |
publisher |
Frontiers Media S.A. |
publishDate |
2020 |
url |
https://doi.org/10.3389/fenvs.2020.00143 https://doaj.org/article/62082c8ecbd842428824536633a06578 |
long_lat |
ENVELOPE(-139.089,-139.089,69.583,69.583) ENVELOPE(-60.917,-60.917,-64.117,-64.117) |
geographic |
Arctic Barents Sea Herschel Island Kay Laptev Sea |
geographic_facet |
Arctic Barents Sea Herschel Island Kay Laptev Sea |
genre |
Arctic Barents Sea Beaufort Sea Herschel Island laptev Laptev Sea permafrost |
genre_facet |
Arctic Barents Sea Beaufort Sea Herschel Island laptev Laptev Sea permafrost |
op_source |
Frontiers in Environmental Science, Vol 8 (2020) |
op_relation |
2296-665X doi:10.3389/fenvs.2020.00143 https://doaj.org/article/62082c8ecbd842428824536633a06578 |
op_rights |
undefined |
op_doi |
https://doi.org/10.3389/fenvs.2020.00143 |
container_title |
Frontiers in Environmental Science |
container_volume |
8 |
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1766324562859917312 |