Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ...
Sea ice monitoring plays a vital role in climate study, maritime navigation and offshore industries. Sea ice monitoring consists of different applications, such as ice classification, concentration and thickness retrieval. As one of the branches of sea ice monitoring, sea ice classification is an es...
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Memorial University of Newfoundland
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Online Access: | https://dx.doi.org/10.48336/3emq-4132 https://research.library.mun.ca/15658/ |
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ftdatacite:10.48336/3emq-4132 2023-05-15T18:16:05+02:00 Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... Lyu, Hangyu 2022 https://dx.doi.org/10.48336/3emq-4132 https://research.library.mun.ca/15658/ en eng Memorial University of Newfoundland Text ScholarlyArticle article-journal 2022 ftdatacite https://doi.org/10.48336/3emq-4132 2023-04-03T16:01:16Z Sea ice monitoring plays a vital role in climate study, maritime navigation and offshore industries. Sea ice monitoring consists of different applications, such as ice classification, concentration and thickness retrieval. As one of the branches of sea ice monitoring, sea ice classification is an essential task in sea ice mapping and the premise to obtain other sea ice parameters. Satellite images are the primary source for sea ice classification due to the broad coverage, the extremely harsh environment in the polar regions and the near real-time requirements of some applications. Spaceborne Synthetic Aperture Radar (SAR) has been widely used as an effective tool for sea ice sensing for decades because it can collect data day and night and in all weather conditions. As a typical representative of the next generation SAR mission, the RADARSAT Constellation Mission (RCM) provides three C-band SAR satellites with shorter revisit time and broader spatial coverage, which will be widely used in various earth ... Text Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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English |
description |
Sea ice monitoring plays a vital role in climate study, maritime navigation and offshore industries. Sea ice monitoring consists of different applications, such as ice classification, concentration and thickness retrieval. As one of the branches of sea ice monitoring, sea ice classification is an essential task in sea ice mapping and the premise to obtain other sea ice parameters. Satellite images are the primary source for sea ice classification due to the broad coverage, the extremely harsh environment in the polar regions and the near real-time requirements of some applications. Spaceborne Synthetic Aperture Radar (SAR) has been widely used as an effective tool for sea ice sensing for decades because it can collect data day and night and in all weather conditions. As a typical representative of the next generation SAR mission, the RADARSAT Constellation Mission (RCM) provides three C-band SAR satellites with shorter revisit time and broader spatial coverage, which will be widely used in various earth ... |
format |
Text |
author |
Lyu, Hangyu |
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Lyu, Hangyu Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
author_facet |
Lyu, Hangyu |
author_sort |
Lyu, Hangyu |
title |
Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
title_short |
Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
title_full |
Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
title_fullStr |
Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
title_full_unstemmed |
Sea ice classification from RADARSAT constellation mission images using normalizer-free ResNet ... |
title_sort |
sea ice classification from radarsat constellation mission images using normalizer-free resnet ... |
publisher |
Memorial University of Newfoundland |
publishDate |
2022 |
url |
https://dx.doi.org/10.48336/3emq-4132 https://research.library.mun.ca/15658/ |
genre |
Sea ice |
genre_facet |
Sea ice |
op_doi |
https://doi.org/10.48336/3emq-4132 |
_version_ |
1766189502572789760 |