Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization

Simulated compact polarimetry from the RADARSAT Constellation Mission (RCM) is evaluated for sea ice classification. Compared to previous studies that evaluated the potential of RCM for sea ice classification, this study focuses on the High Resolution (HR) Synthetic Aperture Radar (SAR) mode of the...

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Published in:Remote Sensing
Main Authors: Mohammed Dabboor, Benoit Montpetit, Stephen Howell
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2018
Subjects:
SAR
Q
Online Access:https://doi.org/10.3390/rs10040594
https://doaj.org/article/4042251201144256ba5318fd61734297
id ftdoajarticles:oai:doaj.org/article:4042251201144256ba5318fd61734297
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spelling ftdoajarticles:oai:doaj.org/article:4042251201144256ba5318fd61734297 2023-05-15T18:17:03+02:00 Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization Mohammed Dabboor Benoit Montpetit Stephen Howell 2018-04-01T00:00:00Z https://doi.org/10.3390/rs10040594 https://doaj.org/article/4042251201144256ba5318fd61734297 EN eng MDPI AG http://www.mdpi.com/2072-4292/10/4/594 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs10040594 https://doaj.org/article/4042251201144256ba5318fd61734297 Remote Sensing, Vol 10, Iss 4, p 594 (2018) SAR compact polarimetry sea ice classification Science Q article 2018 ftdoajarticles https://doi.org/10.3390/rs10040594 2022-12-31T07:29:43Z Simulated compact polarimetry from the RADARSAT Constellation Mission (RCM) is evaluated for sea ice classification. Compared to previous studies that evaluated the potential of RCM for sea ice classification, this study focuses on the High Resolution (HR) Synthetic Aperture Radar (SAR) mode of the RCM associated with a higher noise floor (Noise Equivalent Sigma Zero of −19 dB), which can prove challenging for sea ice monitoring. Twenty three Compact Polarimetric (CP) parameters were derived and analyzed for the discrimination between first year ice (FYI) and multiyear ice (MYI). The results of the RCM HR mode are compared with those previously obtained for other RCM SAR modes for possible CP consistency parameters in sea ice classification under different noise floors, spatial resolutions, and radar incidence angles. Finally, effective CP parameters were identified and used for the classification of FYI and MYI using the Random Forest (RF) classification algorithm. This study indicates that, despite the expected high noise floor of the RCM HR mode, CP SAR data from this mode are promising for the classification of FYI and MYI in dry ice winter conditions. The overall classification accuracies of CP SAR data over two test sites (96.13% and 96.84%) were found to be comparable to the accuracies obtained using Full Polarimetric (FP) SAR data (98.99% and 99.20%). Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Remote Sensing 10 4 594
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic SAR
compact polarimetry
sea ice
classification
Science
Q
spellingShingle SAR
compact polarimetry
sea ice
classification
Science
Q
Mohammed Dabboor
Benoit Montpetit
Stephen Howell
Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
topic_facet SAR
compact polarimetry
sea ice
classification
Science
Q
description Simulated compact polarimetry from the RADARSAT Constellation Mission (RCM) is evaluated for sea ice classification. Compared to previous studies that evaluated the potential of RCM for sea ice classification, this study focuses on the High Resolution (HR) Synthetic Aperture Radar (SAR) mode of the RCM associated with a higher noise floor (Noise Equivalent Sigma Zero of −19 dB), which can prove challenging for sea ice monitoring. Twenty three Compact Polarimetric (CP) parameters were derived and analyzed for the discrimination between first year ice (FYI) and multiyear ice (MYI). The results of the RCM HR mode are compared with those previously obtained for other RCM SAR modes for possible CP consistency parameters in sea ice classification under different noise floors, spatial resolutions, and radar incidence angles. Finally, effective CP parameters were identified and used for the classification of FYI and MYI using the Random Forest (RF) classification algorithm. This study indicates that, despite the expected high noise floor of the RCM HR mode, CP SAR data from this mode are promising for the classification of FYI and MYI in dry ice winter conditions. The overall classification accuracies of CP SAR data over two test sites (96.13% and 96.84%) were found to be comparable to the accuracies obtained using Full Polarimetric (FP) SAR data (98.99% and 99.20%).
format Article in Journal/Newspaper
author Mohammed Dabboor
Benoit Montpetit
Stephen Howell
author_facet Mohammed Dabboor
Benoit Montpetit
Stephen Howell
author_sort Mohammed Dabboor
title Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
title_short Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
title_full Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
title_fullStr Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
title_full_unstemmed Assessment of the High Resolution SAR Mode of the RADARSAT Constellation Mission for First Year Ice and Multiyear Ice Characterization
title_sort assessment of the high resolution sar mode of the radarsat constellation mission for first year ice and multiyear ice characterization
publisher MDPI AG
publishDate 2018
url https://doi.org/10.3390/rs10040594
https://doaj.org/article/4042251201144256ba5318fd61734297
genre Sea ice
genre_facet Sea ice
op_source Remote Sensing, Vol 10, Iss 4, p 594 (2018)
op_relation http://www.mdpi.com/2072-4292/10/4/594
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs10040594
https://doaj.org/article/4042251201144256ba5318fd61734297
op_doi https://doi.org/10.3390/rs10040594
container_title Remote Sensing
container_volume 10
container_issue 4
container_start_page 594
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