Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery
In this study, the extraction of sea ice drift from imagery captured by the 1-meter C-SAR 01 satellite (C-SAR/01) was facilitated utilizing the oriented fast and rotated brief algorithm within the feature tracking procedure, thus addressing the previously unexplored area of sea ice drift...
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ftdoajarticles:oai:doaj.org/article:d95cc4c7d2e8492abfeb443264f2e114 2024-09-15T18:34:06+00:00 Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery Yanli Yang Tao Xie Chengzhi Sun Chao Wang Jian Li Xuehong Zhang 2024-01-01T00:00:00Z https://doi.org/10.1109/JSTARS.2024.3403919 https://doaj.org/article/d95cc4c7d2e8492abfeb443264f2e114 EN eng IEEE https://ieeexplore.ieee.org/document/10536170/ https://doaj.org/toc/1939-1404 https://doaj.org/toc/2151-1535 1939-1404 2151-1535 doi:10.1109/JSTARS.2024.3403919 https://doaj.org/article/d95cc4c7d2e8492abfeb443264f2e114 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10237-10251 (2024) 1-meter C-SAR 01(C-SAR/01) Arctic feature tracking (FT) oriented fast and rotated brief (ORB) sea ice drift synthetic aperture radar (SAR) Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 article 2024 ftdoajarticles https://doi.org/10.1109/JSTARS.2024.3403919 2024-08-05T17:49:07Z In this study, the extraction of sea ice drift from imagery captured by the 1-meter C-SAR 01 satellite (C-SAR/01) was facilitated utilizing the oriented fast and rotated brief algorithm within the feature tracking procedure, thus addressing the previously unexplored area of sea ice drift extraction using C-SAR/01 imagery. The retained keypoints and nearest neighbor distance ratio test for sea ice drift extracted from C-SAR/01 imagery were compared, indicating high reliability with 300 000 and 0.75, respectively. In addition, the local outlier factor algorithm is proposed in this article, which can effectively remove erroneous sea ice drift vectors. The sea ice drift extracted from C-SAR/01 was validated against manually extracted sea ice drift, revealing an uncertainty of 0.271 cm/s in speed and 8.331° in direction. Furthermore, the sea ice drift obtained from the algorithm in this study, when compared with sea ice drift from IABP buoys, exhibits high accuracy, reflecting the robustness of the algorithm. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17 10237 10251 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
1-meter C-SAR 01(C-SAR/01) Arctic feature tracking (FT) oriented fast and rotated brief (ORB) sea ice drift synthetic aperture radar (SAR) Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 |
spellingShingle |
1-meter C-SAR 01(C-SAR/01) Arctic feature tracking (FT) oriented fast and rotated brief (ORB) sea ice drift synthetic aperture radar (SAR) Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 Yanli Yang Tao Xie Chengzhi Sun Chao Wang Jian Li Xuehong Zhang Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
topic_facet |
1-meter C-SAR 01(C-SAR/01) Arctic feature tracking (FT) oriented fast and rotated brief (ORB) sea ice drift synthetic aperture radar (SAR) Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 |
description |
In this study, the extraction of sea ice drift from imagery captured by the 1-meter C-SAR 01 satellite (C-SAR/01) was facilitated utilizing the oriented fast and rotated brief algorithm within the feature tracking procedure, thus addressing the previously unexplored area of sea ice drift extraction using C-SAR/01 imagery. The retained keypoints and nearest neighbor distance ratio test for sea ice drift extracted from C-SAR/01 imagery were compared, indicating high reliability with 300 000 and 0.75, respectively. In addition, the local outlier factor algorithm is proposed in this article, which can effectively remove erroneous sea ice drift vectors. The sea ice drift extracted from C-SAR/01 was validated against manually extracted sea ice drift, revealing an uncertainty of 0.271 cm/s in speed and 8.331° in direction. Furthermore, the sea ice drift obtained from the algorithm in this study, when compared with sea ice drift from IABP buoys, exhibits high accuracy, reflecting the robustness of the algorithm. |
format |
Article in Journal/Newspaper |
author |
Yanli Yang Tao Xie Chengzhi Sun Chao Wang Jian Li Xuehong Zhang |
author_facet |
Yanli Yang Tao Xie Chengzhi Sun Chao Wang Jian Li Xuehong Zhang |
author_sort |
Yanli Yang |
title |
Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
title_short |
Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
title_full |
Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
title_fullStr |
Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
title_full_unstemmed |
Improvement of Sea Ice Drift Extraction Based on Feature Tracking from C-SAR/01 Imagery |
title_sort |
improvement of sea ice drift extraction based on feature tracking from c-sar/01 imagery |
publisher |
IEEE |
publishDate |
2024 |
url |
https://doi.org/10.1109/JSTARS.2024.3403919 https://doaj.org/article/d95cc4c7d2e8492abfeb443264f2e114 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10237-10251 (2024) |
op_relation |
https://ieeexplore.ieee.org/document/10536170/ https://doaj.org/toc/1939-1404 https://doaj.org/toc/2151-1535 1939-1404 2151-1535 doi:10.1109/JSTARS.2024.3403919 https://doaj.org/article/d95cc4c7d2e8492abfeb443264f2e114 |
op_doi |
https://doi.org/10.1109/JSTARS.2024.3403919 |
container_title |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
container_volume |
17 |
container_start_page |
10237 |
op_container_end_page |
10251 |
_version_ |
1810475840601849856 |