Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data
Changes in glacier zones (e.g., firn, superimposed ice, ice) are good indicators of glacier response to climate change. There are few studies of glacier zone detection by SAR that are focused on more than one ice body and validated by terrestrial data. This study is unique in terms of the dataset co...
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2023
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ftdoajarticles:oai:doaj.org/article:23281f057c6f40d3a933ba78b099a6c5 2023-05-15T16:21:40+02:00 Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data Barbara Barzycka Mariusz Grabiec Jacek Jania Małgorzata Błaszczyk Finnur Pálsson Michał Laska Dariusz Ignatiuk Guðfinna Aðalgeirsdóttir 2023-01-01T00:00:00Z https://doi.org/10.3390/rs15030690 https://doaj.org/article/23281f057c6f40d3a933ba78b099a6c5 EN eng MDPI AG https://www.mdpi.com/2072-4292/15/3/690 https://doaj.org/toc/2072-4292 doi:10.3390/rs15030690 2072-4292 https://doaj.org/article/23281f057c6f40d3a933ba78b099a6c5 Remote Sensing, Vol 15, Iss 690, p 690 (2023) glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15030690 2023-02-12T01:25:51Z Changes in glacier zones (e.g., firn, superimposed ice, ice) are good indicators of glacier response to climate change. There are few studies of glacier zone detection by SAR that are focused on more than one ice body and validated by terrestrial data. This study is unique in terms of the dataset collected—four C- and L-band quad-pol satellite SAR images, Ground Penetrating Radar data, shallow glacier cores—and the number of land ice bodies analyzed, namely, three tidewater glaciers in Svalbard and one ice cap in Iceland. The main aim is to assess how well popular methods of SAR analysis perform in distinguishing glacier zones, regardless of factors such as the morphologic differences of the ice bodies, or differences in SAR data. We test and validate three methods of glacier zone detection: (1) Gaussian Mixture Model–Expectation Maximization (GMM-EM) clustering of dual-pol backscattering coefficient (sigma0); (2) GMM-EM of quad-pol Pauli decomposition; and (3) quad-pol H/α Wishart segmentation. The main findings are that the unsupervised classification of both sigma0 and Pauli decomposition are promising methods for distinguishing glacier zones. The former performs better at detecting the firn zone on SAR images, and the latter in the superimposed ice zone. Additionally, C-band SAR data perform better than L-band at detecting firn, but the latter can potentially separate crevasses via the classification of sigma0 or Pauli decomposition. H/α Wishart segmentation resulted in inconsistent results across the tested cases and did not detect crevasses on L-band SAR data. Article in Journal/Newspaper glacier glacier Ice cap Iceland Svalbard Tidewater Directory of Open Access Journals: DOAJ Articles Svalbard Remote Sensing 15 3 690 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart Science Q |
spellingShingle |
glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart Science Q Barbara Barzycka Mariusz Grabiec Jacek Jania Małgorzata Błaszczyk Finnur Pálsson Michał Laska Dariusz Ignatiuk Guðfinna Aðalgeirsdóttir Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
topic_facet |
glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart Science Q |
description |
Changes in glacier zones (e.g., firn, superimposed ice, ice) are good indicators of glacier response to climate change. There are few studies of glacier zone detection by SAR that are focused on more than one ice body and validated by terrestrial data. This study is unique in terms of the dataset collected—four C- and L-band quad-pol satellite SAR images, Ground Penetrating Radar data, shallow glacier cores—and the number of land ice bodies analyzed, namely, three tidewater glaciers in Svalbard and one ice cap in Iceland. The main aim is to assess how well popular methods of SAR analysis perform in distinguishing glacier zones, regardless of factors such as the morphologic differences of the ice bodies, or differences in SAR data. We test and validate three methods of glacier zone detection: (1) Gaussian Mixture Model–Expectation Maximization (GMM-EM) clustering of dual-pol backscattering coefficient (sigma0); (2) GMM-EM of quad-pol Pauli decomposition; and (3) quad-pol H/α Wishart segmentation. The main findings are that the unsupervised classification of both sigma0 and Pauli decomposition are promising methods for distinguishing glacier zones. The former performs better at detecting the firn zone on SAR images, and the latter in the superimposed ice zone. Additionally, C-band SAR data perform better than L-band at detecting firn, but the latter can potentially separate crevasses via the classification of sigma0 or Pauli decomposition. H/α Wishart segmentation resulted in inconsistent results across the tested cases and did not detect crevasses on L-band SAR data. |
format |
Article in Journal/Newspaper |
author |
Barbara Barzycka Mariusz Grabiec Jacek Jania Małgorzata Błaszczyk Finnur Pálsson Michał Laska Dariusz Ignatiuk Guðfinna Aðalgeirsdóttir |
author_facet |
Barbara Barzycka Mariusz Grabiec Jacek Jania Małgorzata Błaszczyk Finnur Pálsson Michał Laska Dariusz Ignatiuk Guðfinna Aðalgeirsdóttir |
author_sort |
Barbara Barzycka |
title |
Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
title_short |
Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
title_full |
Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
title_fullStr |
Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
title_full_unstemmed |
Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data |
title_sort |
comparison of three methods for distinguishing glacier zones using satellite sar data |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15030690 https://doaj.org/article/23281f057c6f40d3a933ba78b099a6c5 |
geographic |
Svalbard |
geographic_facet |
Svalbard |
genre |
glacier glacier Ice cap Iceland Svalbard Tidewater |
genre_facet |
glacier glacier Ice cap Iceland Svalbard Tidewater |
op_source |
Remote Sensing, Vol 15, Iss 690, p 690 (2023) |
op_relation |
https://www.mdpi.com/2072-4292/15/3/690 https://doaj.org/toc/2072-4292 doi:10.3390/rs15030690 2072-4292 https://doaj.org/article/23281f057c6f40d3a933ba78b099a6c5 |
op_doi |
https://doi.org/10.3390/rs15030690 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
3 |
container_start_page |
690 |
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1766009657348849664 |