Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands
Permafrost thaw resulting from climate warming is threatening to release carbon from high latitude peatlands. The aim of this research was to determine subsidence rates linked to permafrost thaw in sub-Arctic peatlands in Sweden using historical orthophotographic (orthophotos), Unoccupied Aerial Veh...
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ftmdpi:oai:mdpi.com:/2072-4292/14/3/444/ 2023-08-20T04:04:20+02:00 Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands Betsabe de la Barreda-Bautista Doreen S. Boyd Martha Ledger Matthias B. Siewert Chris Chandler Andrew V. Bradley David Gee David J. Large Johan Olofsson Andrew Sowter Sofie Sjögersten agris 2022-01-18 application/pdf https://doi.org/10.3390/rs14030444 EN eng Multidisciplinary Digital Publishing Institute Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs14030444 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 3; Pages: 444 permafrost peatland InSAR Text 2022 ftmdpi https://doi.org/10.3390/rs14030444 2023-08-01T03:52:22Z Permafrost thaw resulting from climate warming is threatening to release carbon from high latitude peatlands. The aim of this research was to determine subsidence rates linked to permafrost thaw in sub-Arctic peatlands in Sweden using historical orthophotographic (orthophotos), Unoccupied Aerial Vehicle (UAV), and Interferometric Synthetic Aperture Radar (InSAR) data. The orthophotos showed that the permafrost palsa on the study sites have been contracting in their areal extent, with the greatest rates of loss between 2002 and 2008. The surface motion estimated from differential digital elevation models from the UAV data showed high levels of subsidence (maximum of −25 cm between 2017 and 2020) around the edges of the raised palsa plateaus. The InSAR data analysis showed that raised palsa areas had the greatest subsidence rates, with maximum subsidence rates of 1.5 cm between 2017 and 2020; however, all wetland vegetation types showed subsidence. We suggest that the difference in spatial units associated with each sensor explains parts of the variation in the subsidence levels recorded. We conclude that InSAR was able to identify the areas most at risk of subsidence and that it can be used to investigate subsidence over large spatial extents, whereas UAV data can be used to better understand the dynamics of permafrost degradation at a local level. These findings underpin a monitoring approach for these peatlands. Text Arctic palsa permafrost MDPI Open Access Publishing Arctic Remote Sensing 14 3 444 |
institution |
Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
permafrost peatland InSAR |
spellingShingle |
permafrost peatland InSAR Betsabe de la Barreda-Bautista Doreen S. Boyd Martha Ledger Matthias B. Siewert Chris Chandler Andrew V. Bradley David Gee David J. Large Johan Olofsson Andrew Sowter Sofie Sjögersten Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
topic_facet |
permafrost peatland InSAR |
description |
Permafrost thaw resulting from climate warming is threatening to release carbon from high latitude peatlands. The aim of this research was to determine subsidence rates linked to permafrost thaw in sub-Arctic peatlands in Sweden using historical orthophotographic (orthophotos), Unoccupied Aerial Vehicle (UAV), and Interferometric Synthetic Aperture Radar (InSAR) data. The orthophotos showed that the permafrost palsa on the study sites have been contracting in their areal extent, with the greatest rates of loss between 2002 and 2008. The surface motion estimated from differential digital elevation models from the UAV data showed high levels of subsidence (maximum of −25 cm between 2017 and 2020) around the edges of the raised palsa plateaus. The InSAR data analysis showed that raised palsa areas had the greatest subsidence rates, with maximum subsidence rates of 1.5 cm between 2017 and 2020; however, all wetland vegetation types showed subsidence. We suggest that the difference in spatial units associated with each sensor explains parts of the variation in the subsidence levels recorded. We conclude that InSAR was able to identify the areas most at risk of subsidence and that it can be used to investigate subsidence over large spatial extents, whereas UAV data can be used to better understand the dynamics of permafrost degradation at a local level. These findings underpin a monitoring approach for these peatlands. |
format |
Text |
author |
Betsabe de la Barreda-Bautista Doreen S. Boyd Martha Ledger Matthias B. Siewert Chris Chandler Andrew V. Bradley David Gee David J. Large Johan Olofsson Andrew Sowter Sofie Sjögersten |
author_facet |
Betsabe de la Barreda-Bautista Doreen S. Boyd Martha Ledger Matthias B. Siewert Chris Chandler Andrew V. Bradley David Gee David J. Large Johan Olofsson Andrew Sowter Sofie Sjögersten |
author_sort |
Betsabe de la Barreda-Bautista |
title |
Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
title_short |
Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
title_full |
Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
title_fullStr |
Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
title_full_unstemmed |
Towards a Monitoring Approach for Understanding Permafrost Degradation and Linked Subsidence in Arctic Peatlands |
title_sort |
towards a monitoring approach for understanding permafrost degradation and linked subsidence in arctic peatlands |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14030444 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic palsa permafrost |
genre_facet |
Arctic palsa permafrost |
op_source |
Remote Sensing; Volume 14; Issue 3; Pages: 444 |
op_relation |
Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs14030444 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14030444 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
3 |
container_start_page |
444 |
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1774714724482547712 |