Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales
Quantification of active-layer thickness (ALT) over seasonally frozen terrains is critical to understand the impacts of climate warming on permafrost ecosystems in cold regions. Current large-scale process-based models cannot characterize the heterogeneous response of local landscapes to homogeneous...
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Online Access: | https://doi.org/10.1088/1748-9326/ad31dc https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f |
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ftdoajarticles:oai:doaj.org/article:f631f6c334ec455098a37bba1ec08b7f 2024-09-15T17:34:49+00:00 Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales Caiyun Zhang Thomas A Douglas David Brodylo Lauren V Bosche M Torre Jorgenson 2024-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/ad31dc https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f EN eng IOP Publishing https://doi.org/10.1088/1748-9326/ad31dc https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ad31dc 1748-9326 https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f Environmental Research Letters, Vol 19, Iss 4, p 044030 (2024) permafrost active-layer thickness estimation remote sensing Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2024 ftdoajarticles https://doi.org/10.1088/1748-9326/ad31dc 2024-08-05T17:49:47Z Quantification of active-layer thickness (ALT) over seasonally frozen terrains is critical to understand the impacts of climate warming on permafrost ecosystems in cold regions. Current large-scale process-based models cannot characterize the heterogeneous response of local landscapes to homogeneous climatic forcing. Here we linked a climate-permafrost model with a machine learning solution to indirectly quantify soil conditions reflected in the edaphic factor using high resolution remote sensor products, and then effectively estimated ALT across space and time down to local scales. Our nine-year field measurements during 2014–2022 and coincident high resolution airborne hyperspectral, lidar, and spaceborne sensor products provided a unique opportunity to test the developed protocol across two permafrost experiment stations in lowland terrains of Interior Alaska. Our developed model could explain over 60% of the variance of the field measured ALT for estimating the shallowest and deepest ALT in 2015 and 2019, suggesting the potential of the designed procedure for projecting local varying terrain response to long-term climate warming scenarios. This work will enhance the National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment’s mission of combining field, airborne, and spaceborne sensor products to understand the coupling of permafrost ecosystems and climate change. Article in Journal/Newspaper Active layer thickness Climate change permafrost Alaska Directory of Open Access Journals: DOAJ Articles Environmental Research Letters 19 4 044030 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
permafrost active-layer thickness estimation remote sensing Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
spellingShingle |
permafrost active-layer thickness estimation remote sensing Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 Caiyun Zhang Thomas A Douglas David Brodylo Lauren V Bosche M Torre Jorgenson Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
topic_facet |
permafrost active-layer thickness estimation remote sensing Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
description |
Quantification of active-layer thickness (ALT) over seasonally frozen terrains is critical to understand the impacts of climate warming on permafrost ecosystems in cold regions. Current large-scale process-based models cannot characterize the heterogeneous response of local landscapes to homogeneous climatic forcing. Here we linked a climate-permafrost model with a machine learning solution to indirectly quantify soil conditions reflected in the edaphic factor using high resolution remote sensor products, and then effectively estimated ALT across space and time down to local scales. Our nine-year field measurements during 2014–2022 and coincident high resolution airborne hyperspectral, lidar, and spaceborne sensor products provided a unique opportunity to test the developed protocol across two permafrost experiment stations in lowland terrains of Interior Alaska. Our developed model could explain over 60% of the variance of the field measured ALT for estimating the shallowest and deepest ALT in 2015 and 2019, suggesting the potential of the designed procedure for projecting local varying terrain response to long-term climate warming scenarios. This work will enhance the National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment’s mission of combining field, airborne, and spaceborne sensor products to understand the coupling of permafrost ecosystems and climate change. |
format |
Article in Journal/Newspaper |
author |
Caiyun Zhang Thomas A Douglas David Brodylo Lauren V Bosche M Torre Jorgenson |
author_facet |
Caiyun Zhang Thomas A Douglas David Brodylo Lauren V Bosche M Torre Jorgenson |
author_sort |
Caiyun Zhang |
title |
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
title_short |
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
title_full |
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
title_fullStr |
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
title_full_unstemmed |
Combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
title_sort |
combining a climate-permafrost model with fine resolution remote sensor products to quantify active-layer thickness at local scales |
publisher |
IOP Publishing |
publishDate |
2024 |
url |
https://doi.org/10.1088/1748-9326/ad31dc https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f |
genre |
Active layer thickness Climate change permafrost Alaska |
genre_facet |
Active layer thickness Climate change permafrost Alaska |
op_source |
Environmental Research Letters, Vol 19, Iss 4, p 044030 (2024) |
op_relation |
https://doi.org/10.1088/1748-9326/ad31dc https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ad31dc 1748-9326 https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f |
op_doi |
https://doi.org/10.1088/1748-9326/ad31dc |
container_title |
Environmental Research Letters |
container_volume |
19 |
container_issue |
4 |
container_start_page |
044030 |
_version_ |
1810295483085619200 |