Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska
Abstract The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can ca...
Published in: | Environmental Research Letters |
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Online Access: | http://dx.doi.org/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6/pdf |
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crioppubl:10.1088/1748-9326/acabd6 2024-06-02T08:08:01+00:00 Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska Zhang, Caiyun Douglas, Thomas A Brodylo, David Jorgenson, M Torre the U.S. Department of Energy, Office of Science U.S. Department of Defense U.S. Army Corps of Engineers Engineer Research and Development Center 2023 http://dx.doi.org/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6/pdf unknown IOP Publishing http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining Environmental Research Letters volume 18, issue 1, page 015003 ISSN 1748-9326 journal-article 2023 crioppubl https://doi.org/10.1088/1748-9326/acabd6 2024-05-07T13:59:11Z Abstract The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can cause dramatic top–down thaw. A challenge in understanding this is to quantify fire-induced thaw settlement at large scales (>1000 km 2 ). In this study, we explored the potential of using Landsat products for a large-scale estimation of fire-induced thaw settlement across a well-studied area representative of ice-rich lowland permafrost in interior Alaska. Six large fires have affected ∼1250 km 2 of the area since 2000. We first identified the linkage of fires, burn severity, and land cover response, and then developed an object-based machine learning ensemble approach to estimate fire-induced thaw settlement by relating airborne repeat lidar data to Landsat products. The model delineated thaw settlement patterns across the six fire scars and explained ∼65% of the variance in lidar-detected elevation change. Our results indicate a combined application of airborne repeat lidar and Landsat products is a valuable tool for large scale quantification of fire-induced thaw settlement. Article in Journal/Newspaper Ice permafrost Alaska IOP Publishing Environmental Research Letters 18 1 015003 |
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Abstract The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can cause dramatic top–down thaw. A challenge in understanding this is to quantify fire-induced thaw settlement at large scales (>1000 km 2 ). In this study, we explored the potential of using Landsat products for a large-scale estimation of fire-induced thaw settlement across a well-studied area representative of ice-rich lowland permafrost in interior Alaska. Six large fires have affected ∼1250 km 2 of the area since 2000. We first identified the linkage of fires, burn severity, and land cover response, and then developed an object-based machine learning ensemble approach to estimate fire-induced thaw settlement by relating airborne repeat lidar data to Landsat products. The model delineated thaw settlement patterns across the six fire scars and explained ∼65% of the variance in lidar-detected elevation change. Our results indicate a combined application of airborne repeat lidar and Landsat products is a valuable tool for large scale quantification of fire-induced thaw settlement. |
author2 |
the U.S. Department of Energy, Office of Science U.S. Department of Defense U.S. Army Corps of Engineers Engineer Research and Development Center |
format |
Article in Journal/Newspaper |
author |
Zhang, Caiyun Douglas, Thomas A Brodylo, David Jorgenson, M Torre |
spellingShingle |
Zhang, Caiyun Douglas, Thomas A Brodylo, David Jorgenson, M Torre Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
author_facet |
Zhang, Caiyun Douglas, Thomas A Brodylo, David Jorgenson, M Torre |
author_sort |
Zhang, Caiyun |
title |
Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
title_short |
Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
title_full |
Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
title_fullStr |
Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
title_full_unstemmed |
Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska |
title_sort |
linking repeat lidar with landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior alaska |
publisher |
IOP Publishing |
publishDate |
2023 |
url |
http://dx.doi.org/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6 https://iopscience.iop.org/article/10.1088/1748-9326/acabd6/pdf |
genre |
Ice permafrost Alaska |
genre_facet |
Ice permafrost Alaska |
op_source |
Environmental Research Letters volume 18, issue 1, page 015003 ISSN 1748-9326 |
op_rights |
http://creativecommons.org/licenses/by/4.0 https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/1748-9326/acabd6 |
container_title |
Environmental Research Letters |
container_volume |
18 |
container_issue |
1 |
container_start_page |
015003 |
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1800753167732834304 |