A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data
Sea ice drift strongly influences sea ice thickness distribution and indirectly controls air-sea ice-ocean interactions. Estimating sea ice drift over a large range of spatial and temporal scales is therefore needed to characterize the properties of sea ice dynamics and to better understand the ongo...
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ftdoajarticles:oai:doaj.org/article:83e6ca9906eb411687d509f3c176e0da 2023-05-15T18:16:13+02:00 A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data Anton Andreevich Korosov Pierre Rampal 2017-03-01T00:00:00Z https://doi.org/10.3390/rs9030258 https://doaj.org/article/83e6ca9906eb411687d509f3c176e0da EN eng MDPI AG http://www.mdpi.com/2072-4292/9/3/258 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9030258 https://doaj.org/article/83e6ca9906eb411687d509f3c176e0da Remote Sensing, Vol 9, Iss 3, p 258 (2017) sea ice drift feature tracking pattern matching Sentinel-1 SAR Science Q article 2017 ftdoajarticles https://doi.org/10.3390/rs9030258 2022-12-31T16:18:23Z Sea ice drift strongly influences sea ice thickness distribution and indirectly controls air-sea ice-ocean interactions. Estimating sea ice drift over a large range of spatial and temporal scales is therefore needed to characterize the properties of sea ice dynamics and to better understand the ongoing changes of the climate in the polar regions. An efficient algorithm is developed for processing SAR data based on the combination of feature tracking (FT) and pattern matching (PM) techniques. The main advantage of the combination is that the FT rapidly provides the first guess estimate of ice drift in a few unevenly distributed keypoints, and PM accurately provides drift vectors on a regular or irregular grid. Thorough sensitivity analysis of the algorithm is performed, and optimal sets of parameters are suggested for retrieval of sea ice drift on various spatial and temporal scales. The algorithm has rather high accuracy (error is below 300 m) and high speed (the time for one image pair is 1 min), which opens new opportunities for studying sea ice kinematic processes. The ice drift can now be efficiently observed in the Lagrangian coordinate system on an irregular grid and, therefore, used for pointwise evaluation of the models running on unstructured meshes or for assimilation into Lagrangian models. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Remote Sensing 9 3 258 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
sea ice drift feature tracking pattern matching Sentinel-1 SAR Science Q |
spellingShingle |
sea ice drift feature tracking pattern matching Sentinel-1 SAR Science Q Anton Andreevich Korosov Pierre Rampal A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
topic_facet |
sea ice drift feature tracking pattern matching Sentinel-1 SAR Science Q |
description |
Sea ice drift strongly influences sea ice thickness distribution and indirectly controls air-sea ice-ocean interactions. Estimating sea ice drift over a large range of spatial and temporal scales is therefore needed to characterize the properties of sea ice dynamics and to better understand the ongoing changes of the climate in the polar regions. An efficient algorithm is developed for processing SAR data based on the combination of feature tracking (FT) and pattern matching (PM) techniques. The main advantage of the combination is that the FT rapidly provides the first guess estimate of ice drift in a few unevenly distributed keypoints, and PM accurately provides drift vectors on a regular or irregular grid. Thorough sensitivity analysis of the algorithm is performed, and optimal sets of parameters are suggested for retrieval of sea ice drift on various spatial and temporal scales. The algorithm has rather high accuracy (error is below 300 m) and high speed (the time for one image pair is 1 min), which opens new opportunities for studying sea ice kinematic processes. The ice drift can now be efficiently observed in the Lagrangian coordinate system on an irregular grid and, therefore, used for pointwise evaluation of the models running on unstructured meshes or for assimilation into Lagrangian models. |
format |
Article in Journal/Newspaper |
author |
Anton Andreevich Korosov Pierre Rampal |
author_facet |
Anton Andreevich Korosov Pierre Rampal |
author_sort |
Anton Andreevich Korosov |
title |
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
title_short |
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
title_full |
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
title_fullStr |
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
title_full_unstemmed |
A Combination of Feature Tracking and Pattern Matching with Optimal Parametrization for Sea Ice Drift Retrieval from SAR Data |
title_sort |
combination of feature tracking and pattern matching with optimal parametrization for sea ice drift retrieval from sar data |
publisher |
MDPI AG |
publishDate |
2017 |
url |
https://doi.org/10.3390/rs9030258 https://doaj.org/article/83e6ca9906eb411687d509f3c176e0da |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing, Vol 9, Iss 3, p 258 (2017) |
op_relation |
http://www.mdpi.com/2072-4292/9/3/258 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9030258 https://doaj.org/article/83e6ca9906eb411687d509f3c176e0da |
op_doi |
https://doi.org/10.3390/rs9030258 |
container_title |
Remote Sensing |
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9 |
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3 |
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258 |
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1766189683698565120 |