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...

Full description

Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Caiyun Zhang, Thomas A Douglas, David Brodylo, Lauren V Bosche, M Torre Jorgenson
Format: Article in Journal/Newspaper
Language:English
Published: IOP Publishing 2024
Subjects:
Q
Online Access:https://doi.org/10.1088/1748-9326/ad31dc
https://doaj.org/article/f631f6c334ec455098a37bba1ec08b7f
id ftdoajarticles:oai:doaj.org/article:f631f6c334ec455098a37bba1ec08b7f
record_format openpolar
spelling 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