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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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/3/690 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T09:26:51Z |
| format | Article |
| id | doaj.art-23281f057c6f40d3a933ba78b099a6c5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:26:51Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-23281f057c6f40d3a933ba78b099a6c52023-11-16T17:52:51ZengMDPI AGRemote Sensing2072-42922023-01-0115369010.3390/rs15030690Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR DataBarbara Barzycka0Mariusz Grabiec1Jacek Jania2Małgorzata Błaszczyk3Finnur Pálsson4Michał Laska5Dariusz Ignatiuk6Guðfinna Aðalgeirsdóttir7Institute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, University of Iceland, Sturlugata 7, 101 Reykjavík, IcelandInstitute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, Będzinska 60, 41-200 Sosnowiec, PolandInstitute of Earth Sciences, University of Iceland, Sturlugata 7, 101 Reykjavík, IcelandChanges 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.https://www.mdpi.com/2072-4292/15/3/690glacier faciespolarimetryPolSARsigma0PauliH/alpha Wishart |
| spellingShingle | 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 Remote Sensing glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart |
| title | 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_short | 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 |
| topic | glacier facies polarimetry PolSAR sigma0 Pauli H/alpha Wishart |
| url | https://www.mdpi.com/2072-4292/15/3/690 |
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