Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr
Permafrost is warming globally which leads to widespread permafrost thaw. Particularly ice-rich permafrost is vulnerable to rapid thaw and erosion, impacting whole landscapes and ecosystems. Retrogressive thaw slumps (RTS) are abrupt permafrost disturbances that expand by several meters each year an...
Published in: | Remote Sensing of Environment |
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Elsevier
2022
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Online Access: | https://epic.awi.de/id/eprint/54836/ https://epic.awi.de/id/eprint/54836/1/Runge_et_al_RemoteSensing_Annual_Thaw_Dynamics.pdf https://www.sciencedirect.com/science/article/pii/S0034425721004727 https://hdl.handle.net/10013/epic.c8ac90ae-c56e-4b2a-98c7-dae839cd59b1 |
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ftawi:oai:epic.awi.de:54836 2024-03-24T09:02:31+00:00 Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr Runge, Alexandra Nitze, Ingmar Grosse, Guido 2022 application/pdf https://epic.awi.de/id/eprint/54836/ https://epic.awi.de/id/eprint/54836/1/Runge_et_al_RemoteSensing_Annual_Thaw_Dynamics.pdf https://www.sciencedirect.com/science/article/pii/S0034425721004727 https://hdl.handle.net/10013/epic.c8ac90ae-c56e-4b2a-98c7-dae839cd59b1 unknown Elsevier https://epic.awi.de/id/eprint/54836/1/Runge_et_al_RemoteSensing_Annual_Thaw_Dynamics.pdf Runge, A. orcid:0000-0001-5047-0105 , Nitze, I. orcid:0000-0002-1165-6852 and Grosse, G. orcid:0000-0001-5895-2141 (2022) Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr , Remote Sensing of Environment, 268 , p. 112752 . doi:10.1016/j.rse.2021.112752 <https://doi.org/10.1016/j.rse.2021.112752> , hdl:10013/epic.c8ac90ae-c56e-4b2a-98c7-dae839cd59b1 info:eu-repo/semantics/openAccess EPIC3Remote Sensing of Environment, Elsevier, 268, pp. 112752-112752, ISSN: 0034-4257 Article peerRev info:eu-repo/semantics/article 2022 ftawi https://doi.org/10.1016/j.rse.2021.112752 2024-02-27T09:55:26Z Permafrost is warming globally which leads to widespread permafrost thaw. Particularly ice-rich permafrost is vulnerable to rapid thaw and erosion, impacting whole landscapes and ecosystems. Retrogressive thaw slumps (RTS) are abrupt permafrost disturbances that expand by several meters each year and lead to an increased soil organic carbon release. Local Remote Sensing studies identified increasing RTS activity in the last two decades by increasing number of RTS or heightened RTS growth rates. However, a large-scale assessment across diverse permafrost regions and at high temporal resolution allowing to further determine RTS thaw dynamics and its main drivers is still lacking. In this study we apply the disturbance detection algorithm LandTrendr for automated large-scale RTS mapping and high temporal thaw dynamic assessment to North Siberia (8.1×106km2). We adapted and parametrised the temporal segmentation algorithm for abrupt disturbance detection to incorporate Landsat+Sentinel-2 mosaics, conducted spectral filtering, spatial masking and filtering, and a binary machine-learning object classification of the disturbance output to separate between RTS and false positives (F1 score: 0.609). Ground truth data for calibration and validation of the workflow was collected from 9 known RTS cluster sites using very high-resolution RapidEye and PlanetScope imagery. Our study presents the first automated detection and assessment of RTS and their temporal dynamics at large-scale for 2001–2019. We identified 50,895 RTS and a steady increase in RTS-affected area from 2001 to 2019 across North Siberia, with a more abrupt increase from 2016 onward. Overall the RTS-affected area increased by 331 compared to 2000 (2000: 20,158ha, 2001–2019: 66,699ha). Contrary to this, 5 focus sites show spatio-temporal variability in their annual RTS dynamics, with alternating periods of increased and decreased RTS development, indicating a close relationship to thaw drivers. The majority of identified RTS was active from 2000 onward and only ... Article in Journal/Newspaper Ice permafrost Siberia Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Remote Sensing of Environment 268 112752 |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
Permafrost is warming globally which leads to widespread permafrost thaw. Particularly ice-rich permafrost is vulnerable to rapid thaw and erosion, impacting whole landscapes and ecosystems. Retrogressive thaw slumps (RTS) are abrupt permafrost disturbances that expand by several meters each year and lead to an increased soil organic carbon release. Local Remote Sensing studies identified increasing RTS activity in the last two decades by increasing number of RTS or heightened RTS growth rates. However, a large-scale assessment across diverse permafrost regions and at high temporal resolution allowing to further determine RTS thaw dynamics and its main drivers is still lacking. In this study we apply the disturbance detection algorithm LandTrendr for automated large-scale RTS mapping and high temporal thaw dynamic assessment to North Siberia (8.1×106km2). We adapted and parametrised the temporal segmentation algorithm for abrupt disturbance detection to incorporate Landsat+Sentinel-2 mosaics, conducted spectral filtering, spatial masking and filtering, and a binary machine-learning object classification of the disturbance output to separate between RTS and false positives (F1 score: 0.609). Ground truth data for calibration and validation of the workflow was collected from 9 known RTS cluster sites using very high-resolution RapidEye and PlanetScope imagery. Our study presents the first automated detection and assessment of RTS and their temporal dynamics at large-scale for 2001–2019. We identified 50,895 RTS and a steady increase in RTS-affected area from 2001 to 2019 across North Siberia, with a more abrupt increase from 2016 onward. Overall the RTS-affected area increased by 331 compared to 2000 (2000: 20,158ha, 2001–2019: 66,699ha). Contrary to this, 5 focus sites show spatio-temporal variability in their annual RTS dynamics, with alternating periods of increased and decreased RTS development, indicating a close relationship to thaw drivers. The majority of identified RTS was active from 2000 onward and only ... |
format |
Article in Journal/Newspaper |
author |
Runge, Alexandra Nitze, Ingmar Grosse, Guido |
spellingShingle |
Runge, Alexandra Nitze, Ingmar Grosse, Guido Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
author_facet |
Runge, Alexandra Nitze, Ingmar Grosse, Guido |
author_sort |
Runge, Alexandra |
title |
Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
title_short |
Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
title_full |
Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
title_fullStr |
Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
title_full_unstemmed |
Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr |
title_sort |
remote sensing annual dynamics of rapid permafrost thaw disturbances with landtrendr |
publisher |
Elsevier |
publishDate |
2022 |
url |
https://epic.awi.de/id/eprint/54836/ https://epic.awi.de/id/eprint/54836/1/Runge_et_al_RemoteSensing_Annual_Thaw_Dynamics.pdf https://www.sciencedirect.com/science/article/pii/S0034425721004727 https://hdl.handle.net/10013/epic.c8ac90ae-c56e-4b2a-98c7-dae839cd59b1 |
genre |
Ice permafrost Siberia |
genre_facet |
Ice permafrost Siberia |
op_source |
EPIC3Remote Sensing of Environment, Elsevier, 268, pp. 112752-112752, ISSN: 0034-4257 |
op_relation |
https://epic.awi.de/id/eprint/54836/1/Runge_et_al_RemoteSensing_Annual_Thaw_Dynamics.pdf Runge, A. orcid:0000-0001-5047-0105 , Nitze, I. orcid:0000-0002-1165-6852 and Grosse, G. orcid:0000-0001-5895-2141 (2022) Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr , Remote Sensing of Environment, 268 , p. 112752 . doi:10.1016/j.rse.2021.112752 <https://doi.org/10.1016/j.rse.2021.112752> , hdl:10013/epic.c8ac90ae-c56e-4b2a-98c7-dae839cd59b1 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1016/j.rse.2021.112752 |
container_title |
Remote Sensing of Environment |
container_volume |
268 |
container_start_page |
112752 |
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1794402869806366720 |