Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data

Accurate information on the extent and dynamics of ice cover is important on a global scale. Owing to the daynight and weather-independent imagery capabilities, Sentinel-1 (S1) is a reliable source for ice monitoring using synthetic aperture radar (SAR) images. Therefore, this study focuses on an un...

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Bibliographic Details
Main Authors: Muhammad Amjad Iqbal, Andrei Anghel, Mihai Datcu
Format: Conference Object
Language:English
Published: Zenodo 2023
Subjects:
SAR
Online Access:https://doi.org/10.5281/zenodo.8246262
id ftzenodo:oai:zenodo.org:8246262
record_format openpolar
spelling ftzenodo:oai:zenodo.org:8246262 2024-09-15T18:03:39+00:00 Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data Muhammad Amjad Iqbal Andrei Anghel Mihai Datcu 2023-10-06 https://doi.org/10.5281/zenodo.8246262 eng eng Zenodo https://zenodo.org/communities/menelaos-nt https://zenodo.org/communities/eu https://doi.org/10.5281/zenodo.8246261 https://doi.org/10.5281/zenodo.8246262 oai:zenodo.org:8246262 info:eu-repo/semantics/restrictedAccess MetroSea, IEEE MetroSea 2023, University of Malta - Valletta Campus., 04-06 Oct 2023 SAR Ice-cover CFAR burr distribution polarimetric info:eu-repo/semantics/conferencePaper 2023 ftzenodo https://doi.org/10.5281/zenodo.824626210.5281/zenodo.8246261 2024-07-25T16:28:54Z Accurate information on the extent and dynamics of ice cover is important on a global scale. Owing to the daynight and weather-independent imagery capabilities, Sentinel-1 (S1) is a reliable source for ice monitoring using synthetic aperture radar (SAR) images. Therefore, this study focuses on an unsupervised method for extracting ice cover by exploiting dual-pol S1 SAR data over Devon Island, which is surrounded by sea. We adopted a constant false alarm rate (CFAR) detector for ice cover detection by examining the empirical distribution of a given metric over a ice region, followed by statistical comparison of the resulting distribution with the theoretical “Burr” distribution to derive the CFAR threshold value. To achieve ice detection, a binary image is first retrieved, and then the ice edges are quantified using the Canny edge detector. To evaluate the effectiveness of the proposed method, we applied it to SAR data from a challenging environment, including terrain, ice, and water. The results were further verified using Sentinel-2 (S2) as the ground truth data, which showed the maximum correlation in the extraction. Our findings demonstrate the validity of the proposed method for ice cover extraction using Sentinel-1 data. Conference Object Devon Island Iceland Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic SAR
Ice-cover
CFAR
burr distribution
polarimetric
spellingShingle SAR
Ice-cover
CFAR
burr distribution
polarimetric
Muhammad Amjad Iqbal
Andrei Anghel
Mihai Datcu
Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
topic_facet SAR
Ice-cover
CFAR
burr distribution
polarimetric
description Accurate information on the extent and dynamics of ice cover is important on a global scale. Owing to the daynight and weather-independent imagery capabilities, Sentinel-1 (S1) is a reliable source for ice monitoring using synthetic aperture radar (SAR) images. Therefore, this study focuses on an unsupervised method for extracting ice cover by exploiting dual-pol S1 SAR data over Devon Island, which is surrounded by sea. We adopted a constant false alarm rate (CFAR) detector for ice cover detection by examining the empirical distribution of a given metric over a ice region, followed by statistical comparison of the resulting distribution with the theoretical “Burr” distribution to derive the CFAR threshold value. To achieve ice detection, a binary image is first retrieved, and then the ice edges are quantified using the Canny edge detector. To evaluate the effectiveness of the proposed method, we applied it to SAR data from a challenging environment, including terrain, ice, and water. The results were further verified using Sentinel-2 (S2) as the ground truth data, which showed the maximum correlation in the extraction. Our findings demonstrate the validity of the proposed method for ice cover extraction using Sentinel-1 data.
format Conference Object
author Muhammad Amjad Iqbal
Andrei Anghel
Mihai Datcu
author_facet Muhammad Amjad Iqbal
Andrei Anghel
Mihai Datcu
author_sort Muhammad Amjad Iqbal
title Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
title_short Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
title_full Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
title_fullStr Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
title_full_unstemmed Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
title_sort ice cover delineation over devon iceland using sentinel polarimetric sar and optical data
publisher Zenodo
publishDate 2023
url https://doi.org/10.5281/zenodo.8246262
genre Devon Island
Iceland
genre_facet Devon Island
Iceland
op_source MetroSea, IEEE MetroSea 2023, University of Malta - Valletta Campus., 04-06 Oct 2023
op_relation https://zenodo.org/communities/menelaos-nt
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.8246261
https://doi.org/10.5281/zenodo.8246262
oai:zenodo.org:8246262
op_rights info:eu-repo/semantics/restrictedAccess
op_doi https://doi.org/10.5281/zenodo.824626210.5281/zenodo.8246261
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