Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry
Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and...
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Online Access: | https://hdl.handle.net/11250/2997557 https://doi.org/10.1016/j.rse.2022.112910 |
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ftunivbergen:oai:bora.uib.no:11250/2997557 2023-05-15T16:37:44+02:00 Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry Wangchuk, Sonam Bolch, Tobias Robson, Benjamin Aubrey 2022 application/pdf https://hdl.handle.net/11250/2997557 https://doi.org/10.1016/j.rse.2022.112910 eng eng Elsevier urn:issn:0034-4257 https://hdl.handle.net/11250/2997557 https://doi.org/10.1016/j.rse.2022.112910 cristin:1999054 Remote Sensing of Environment. 2022, 271:112910. Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no © 2022 The Authors. 112910 Remote Sensing of Environment 271 Journal article Peer reviewed 2022 ftunivbergen https://doi.org/10.1016/j.rse.2022.112910 2023-03-14T17:44:02Z Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer lake area change using a time-series radar backscatter intensity data such as the rapid expansion of Bechung Tsho. The PSI analysis showed that all the ... Article in Journal/Newspaper Ice permafrost University of Bergen: Bergen Open Research Archive (BORA-UiB) Glacial Lake ENVELOPE(-129.463,-129.463,58.259,58.259) Psi ENVELOPE(-63.000,-63.000,-64.300,-64.300) Remote Sensing of Environment 271 112910 |
institution |
Open Polar |
collection |
University of Bergen: Bergen Open Research Archive (BORA-UiB) |
op_collection_id |
ftunivbergen |
language |
English |
description |
Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer lake area change using a time-series radar backscatter intensity data such as the rapid expansion of Bechung Tsho. The PSI analysis showed that all the ... |
format |
Article in Journal/Newspaper |
author |
Wangchuk, Sonam Bolch, Tobias Robson, Benjamin Aubrey |
spellingShingle |
Wangchuk, Sonam Bolch, Tobias Robson, Benjamin Aubrey Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
author_facet |
Wangchuk, Sonam Bolch, Tobias Robson, Benjamin Aubrey |
author_sort |
Wangchuk, Sonam |
title |
Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
title_short |
Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
title_full |
Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
title_fullStr |
Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
title_full_unstemmed |
Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry |
title_sort |
monitoring glacial lake outburst flood susceptibility using sentinel-1 sar data, google earth engine, and persistent scatterer interferometry |
publisher |
Elsevier |
publishDate |
2022 |
url |
https://hdl.handle.net/11250/2997557 https://doi.org/10.1016/j.rse.2022.112910 |
long_lat |
ENVELOPE(-129.463,-129.463,58.259,58.259) ENVELOPE(-63.000,-63.000,-64.300,-64.300) |
geographic |
Glacial Lake Psi |
geographic_facet |
Glacial Lake Psi |
genre |
Ice permafrost |
genre_facet |
Ice permafrost |
op_source |
112910 Remote Sensing of Environment 271 |
op_relation |
urn:issn:0034-4257 https://hdl.handle.net/11250/2997557 https://doi.org/10.1016/j.rse.2022.112910 cristin:1999054 Remote Sensing of Environment. 2022, 271:112910. |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no © 2022 The Authors. |
op_doi |
https://doi.org/10.1016/j.rse.2022.112910 |
container_title |
Remote Sensing of Environment |
container_volume |
271 |
container_start_page |
112910 |
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1766028030334992384 |