An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic

For regional environmental studies it is important to know the location of the fast ice edge which affects the coastal processes in the Arctic. The aim of this study is to develop a new automated method for fast ice delineation from SAR imagery. The method is based on a fine resolution hybrid sea ic...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Valeria Selyuzhenok, Denis Demchev
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
SAR
Q
Online Access:https://doi.org/10.3390/rs13183783
https://doaj.org/article/274c40fb0d734bdfb845964a97f7b1bf
id ftdoajarticles:oai:doaj.org/article:274c40fb0d734bdfb845964a97f7b1bf
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spelling ftdoajarticles:oai:doaj.org/article:274c40fb0d734bdfb845964a97f7b1bf 2023-05-15T13:39:48+02:00 An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic Valeria Selyuzhenok Denis Demchev 2021-09-01T00:00:00Z https://doi.org/10.3390/rs13183783 https://doaj.org/article/274c40fb0d734bdfb845964a97f7b1bf EN eng MDPI AG https://www.mdpi.com/2072-4292/13/18/3783 https://doaj.org/toc/2072-4292 doi:10.3390/rs13183783 2072-4292 https://doaj.org/article/274c40fb0d734bdfb845964a97f7b1bf Remote Sensing, Vol 13, Iss 3783, p 3783 (2021) landfast sea ice stamukha SAR Arctic Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13183783 2022-12-31T15:06:53Z For regional environmental studies it is important to know the location of the fast ice edge which affects the coastal processes in the Arctic. The aim of this study is to develop a new automated method for fast ice delineation from SAR imagery. The method is based on a fine resolution hybrid sea ice tracking algorithm utilizing advantages of feature tracking and cross-correlation approaches. The developed method consists of three main steps: drift field retrieval at sub-kilometer scale, selection of motionless features and edge delineation. The method was tested on a time series of C-band co-polarized (HH) ENVISAT ASAR and Sentinel-1 imagery in the Laptev and East Siberian Seas. The comparison of the retrieved edges with the operational ice charts produced by the Arctic and Antarctic Research Institute (Russia) showed a good agreement between the data sets with a mean distance between the edges of <15 km. Thanks to the high density of the ice drift product, the method allows for detailed fast ice edge delineation. In addition, large stamukhas with horizontal size of tens of kilometers can be detected. The proposed method can be applied for regional fast ice mapping and large stamukhas detection to aid coastal research. Additionally, the method can serve as a tool for operational sea ice mapping. Article in Journal/Newspaper Antarc* Antarctic Arctic and Antarctic Research Institute Arctic laptev Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Antarctic Asar ENVELOPE(134.033,134.033,68.667,68.667) Remote Sensing 13 18 3783
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic landfast sea ice
stamukha
SAR
Arctic
Science
Q
spellingShingle landfast sea ice
stamukha
SAR
Arctic
Science
Q
Valeria Selyuzhenok
Denis Demchev
An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
topic_facet landfast sea ice
stamukha
SAR
Arctic
Science
Q
description For regional environmental studies it is important to know the location of the fast ice edge which affects the coastal processes in the Arctic. The aim of this study is to develop a new automated method for fast ice delineation from SAR imagery. The method is based on a fine resolution hybrid sea ice tracking algorithm utilizing advantages of feature tracking and cross-correlation approaches. The developed method consists of three main steps: drift field retrieval at sub-kilometer scale, selection of motionless features and edge delineation. The method was tested on a time series of C-band co-polarized (HH) ENVISAT ASAR and Sentinel-1 imagery in the Laptev and East Siberian Seas. The comparison of the retrieved edges with the operational ice charts produced by the Arctic and Antarctic Research Institute (Russia) showed a good agreement between the data sets with a mean distance between the edges of <15 km. Thanks to the high density of the ice drift product, the method allows for detailed fast ice edge delineation. In addition, large stamukhas with horizontal size of tens of kilometers can be detected. The proposed method can be applied for regional fast ice mapping and large stamukhas detection to aid coastal research. Additionally, the method can serve as a tool for operational sea ice mapping.
format Article in Journal/Newspaper
author Valeria Selyuzhenok
Denis Demchev
author_facet Valeria Selyuzhenok
Denis Demchev
author_sort Valeria Selyuzhenok
title An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
title_short An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
title_full An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
title_fullStr An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
title_full_unstemmed An Application of Sea Ice Tracking Algorithm for Fast Ice and Stamukhas Detection in the Arctic
title_sort application of sea ice tracking algorithm for fast ice and stamukhas detection in the arctic
publisher MDPI AG
publishDate 2021
url https://doi.org/10.3390/rs13183783
https://doaj.org/article/274c40fb0d734bdfb845964a97f7b1bf
long_lat ENVELOPE(134.033,134.033,68.667,68.667)
geographic Arctic
Antarctic
Asar
geographic_facet Arctic
Antarctic
Asar
genre Antarc*
Antarctic
Arctic and Antarctic Research Institute
Arctic
laptev
Sea ice
genre_facet Antarc*
Antarctic
Arctic and Antarctic Research Institute
Arctic
laptev
Sea ice
op_source Remote Sensing, Vol 13, Iss 3783, p 3783 (2021)
op_relation https://www.mdpi.com/2072-4292/13/18/3783
https://doaj.org/toc/2072-4292
doi:10.3390/rs13183783
2072-4292
https://doaj.org/article/274c40fb0d734bdfb845964a97f7b1bf
op_doi https://doi.org/10.3390/rs13183783
container_title Remote Sensing
container_volume 13
container_issue 18
container_start_page 3783
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