Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic
Detailed information on the land cover types present and the horizontal position of the land–water interface is needed for sensitive coastal ecosystems throughout the Arctic, both to establish baselines against which the impacts of climate change can be assessed and to inform response operations in...
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Online Access: | https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/17263 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-172630 https://doi.org/10.3390/rs9121206 https://opus.bibliothek.uni-wuerzburg.de/files/17263/Banks_remotesensing-09-01206.pdf |
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ftunivwuerz:oai:opus.bibliothek.uni-wuerzburg.de:17263 2023-09-05T13:17:05+02:00 Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic Banks, Sarah Millard, Koreen Behnamian, Amir White, Lori Ullmann, Tobias Charbonneau, Francois Chen, Zhaohua Wang, Huili Pasher, Jon Duffe, Jason 2017 application/pdf https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/17263 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-172630 https://doi.org/10.3390/rs9121206 https://opus.bibliothek.uni-wuerzburg.de/files/17263/Banks_remotesensing-09-01206.pdf eng eng https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/17263 urn:nbn:de:bvb:20-opus-172630 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-172630 https://doi.org/10.3390/rs9121206 https://opus.bibliothek.uni-wuerzburg.de/files/17263/Banks_remotesensing-09-01206.pdf https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess ddc:526 article doc-type:article 2017 ftunivwuerz https://doi.org/10.3390/rs9121206 2023-08-13T22:33:53Z Detailed information on the land cover types present and the horizontal position of the land–water interface is needed for sensitive coastal ecosystems throughout the Arctic, both to establish baselines against which the impacts of climate change can be assessed and to inform response operations in the event of environmental emergencies such as oil spills. Previous work has demonstrated potential for accurate classification via fusion of optical and SAR data, though what contribution either makes to model accuracy is not well established, nor is it clear what shorelines can be classified using optical or SAR data alone. In this research, we evaluate the relative value of quad pol RADARSAT-2 and Landsat 5 data for shoreline mapping by individually excluding both datasets from Random Forest models used to classify images acquired over Nunavut, Canada. In anticipation of the RADARSAT Constellation Mission (RCM), we also simulate and evaluate dual and compact polarimetric imagery for shoreline mapping. Results show that SAR data is needed for accurate discrimination of substrates as user’s and producer’s accuracies were 5–24% higher for models constructed with quad pol RADARSAT-2 and DEM data than models constructed with Landsat 5 and DEM data. Models based on simulated RCM and DEM data achieved significantly lower overall accuracies (71–77%) than models based on quad pol RADARSAT-2 and DEM data (80%), with Wetland and Tundra being most adversely affected. When classified together with Landsat 5 and DEM data, however, model accuracy was less affected by the SAR data type, with multiple polarizations and modes achieving independent overall accuracies within a range acceptable for operational mapping, at 89–91%. RCM is expected to contribute positively to ongoing efforts to monitor change and improve emergency preparedness throughout the Arctic. Article in Journal/Newspaper Arctic Climate change Nunavut Tundra Würzburg University: Online Publication Service Arctic Canada Nunavut Remote Sensing 9 12 1206 |
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Open Polar |
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Würzburg University: Online Publication Service |
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ftunivwuerz |
language |
English |
topic |
ddc:526 |
spellingShingle |
ddc:526 Banks, Sarah Millard, Koreen Behnamian, Amir White, Lori Ullmann, Tobias Charbonneau, Francois Chen, Zhaohua Wang, Huili Pasher, Jon Duffe, Jason Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
topic_facet |
ddc:526 |
description |
Detailed information on the land cover types present and the horizontal position of the land–water interface is needed for sensitive coastal ecosystems throughout the Arctic, both to establish baselines against which the impacts of climate change can be assessed and to inform response operations in the event of environmental emergencies such as oil spills. Previous work has demonstrated potential for accurate classification via fusion of optical and SAR data, though what contribution either makes to model accuracy is not well established, nor is it clear what shorelines can be classified using optical or SAR data alone. In this research, we evaluate the relative value of quad pol RADARSAT-2 and Landsat 5 data for shoreline mapping by individually excluding both datasets from Random Forest models used to classify images acquired over Nunavut, Canada. In anticipation of the RADARSAT Constellation Mission (RCM), we also simulate and evaluate dual and compact polarimetric imagery for shoreline mapping. Results show that SAR data is needed for accurate discrimination of substrates as user’s and producer’s accuracies were 5–24% higher for models constructed with quad pol RADARSAT-2 and DEM data than models constructed with Landsat 5 and DEM data. Models based on simulated RCM and DEM data achieved significantly lower overall accuracies (71–77%) than models based on quad pol RADARSAT-2 and DEM data (80%), with Wetland and Tundra being most adversely affected. When classified together with Landsat 5 and DEM data, however, model accuracy was less affected by the SAR data type, with multiple polarizations and modes achieving independent overall accuracies within a range acceptable for operational mapping, at 89–91%. RCM is expected to contribute positively to ongoing efforts to monitor change and improve emergency preparedness throughout the Arctic. |
format |
Article in Journal/Newspaper |
author |
Banks, Sarah Millard, Koreen Behnamian, Amir White, Lori Ullmann, Tobias Charbonneau, Francois Chen, Zhaohua Wang, Huili Pasher, Jon Duffe, Jason |
author_facet |
Banks, Sarah Millard, Koreen Behnamian, Amir White, Lori Ullmann, Tobias Charbonneau, Francois Chen, Zhaohua Wang, Huili Pasher, Jon Duffe, Jason |
author_sort |
Banks, Sarah |
title |
Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
title_short |
Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
title_full |
Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
title_fullStr |
Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
title_full_unstemmed |
Contributions of actual and simulated satellite SAR data for substrate type differentiation and shoreline mapping in the Canadian Arctic |
title_sort |
contributions of actual and simulated satellite sar data for substrate type differentiation and shoreline mapping in the canadian arctic |
publishDate |
2017 |
url |
https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/17263 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-172630 https://doi.org/10.3390/rs9121206 https://opus.bibliothek.uni-wuerzburg.de/files/17263/Banks_remotesensing-09-01206.pdf |
geographic |
Arctic Canada Nunavut |
geographic_facet |
Arctic Canada Nunavut |
genre |
Arctic Climate change Nunavut Tundra |
genre_facet |
Arctic Climate change Nunavut Tundra |
op_relation |
https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/17263 urn:nbn:de:bvb:20-opus-172630 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-172630 https://doi.org/10.3390/rs9121206 https://opus.bibliothek.uni-wuerzburg.de/files/17263/Banks_remotesensing-09-01206.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/rs9121206 |
container_title |
Remote Sensing |
container_volume |
9 |
container_issue |
12 |
container_start_page |
1206 |
_version_ |
1776198399858573312 |