Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques

Quantifying end of summer season Active Layer Thickness (ALT) of permafrost is critical for understanding the effects of climate warming, disturbance, and hydrologic changes on permafrost. Current research mainly focuses on ALT estimation and mapping at large scales using process-based or statistica...

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Bibliographic Details
Published in:International Journal of Applied Earth Observation and Geoinformation
Main Authors: Caiyun Zhang, Thomas A. Douglas, John E. Anderson
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2021
Subjects:
geo
Online Access:https://doi.org/10.1016/j.jag.2021.102455
https://doaj.org/article/f13ff21226f541369424fbf312bbbacc
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:f13ff21226f541369424fbf312bbbacc 2023-05-15T13:02:59+02:00 Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques Caiyun Zhang Thomas A. Douglas John E. Anderson 2021-10-01 https://doi.org/10.1016/j.jag.2021.102455 https://doaj.org/article/f13ff21226f541369424fbf312bbbacc en eng Elsevier 1569-8432 doi:10.1016/j.jag.2021.102455 https://doaj.org/article/f13ff21226f541369424fbf312bbbacc undefined International Journal of Applied Earth Observations and Geoinformation, Vol 102, Iss , Pp 102455- (2021) Permafrost active layer Hyperspectral imaging Machine learning modeling and mapping geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2021 fttriple https://doi.org/10.1016/j.jag.2021.102455 2023-01-22T19:11:37Z Quantifying end of summer season Active Layer Thickness (ALT) of permafrost is critical for understanding the effects of climate warming, disturbance, and hydrologic changes on permafrost. Current research mainly focuses on ALT estimation and mapping at large scales using process-based or statistical-empirical models with biophysical variables as predictors. Here we modeled multi-year ALT field measurements between 2014 and 2019 at a site in Interior Alaska using 1-m hyperspectral imaging data and an object-based ensemble approach at a local scale (1 km2), examined the efficacy of the multispectral sensor WorldView (WV)-2 for ALT estimation, and explored the potential of integrating single-date imaging data with multi-year in-situ measurements for mapping the spatial and temporal variation of ALT. Modeling results showed hyperspectral imaging was accurate for estimating ALT with a correlation coefficient (r) larger than 0.7, while application of WV-2 data produced an r around 0.4. Reasonable ALT patterns were generated, and the spatial and temporal variation of ALT was delineated between the shallowest (2015) and deepest (2019) years using hyperspectral data. This study suggests hyperspectral imaging is a promising tool for predicting field ALT measurements and monitoring ALT change at local scales. We expect this study will stimulate hyperspectral optical sensors for permafrost studies in general, and particularly for ALT upscaling. Article in Journal/Newspaper Active layer thickness permafrost Alaska Unknown International Journal of Applied Earth Observation and Geoinformation 102 102455
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic Permafrost active layer
Hyperspectral imaging
Machine learning modeling and mapping
geo
envir
spellingShingle Permafrost active layer
Hyperspectral imaging
Machine learning modeling and mapping
geo
envir
Caiyun Zhang
Thomas A. Douglas
John E. Anderson
Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
topic_facet Permafrost active layer
Hyperspectral imaging
Machine learning modeling and mapping
geo
envir
description Quantifying end of summer season Active Layer Thickness (ALT) of permafrost is critical for understanding the effects of climate warming, disturbance, and hydrologic changes on permafrost. Current research mainly focuses on ALT estimation and mapping at large scales using process-based or statistical-empirical models with biophysical variables as predictors. Here we modeled multi-year ALT field measurements between 2014 and 2019 at a site in Interior Alaska using 1-m hyperspectral imaging data and an object-based ensemble approach at a local scale (1 km2), examined the efficacy of the multispectral sensor WorldView (WV)-2 for ALT estimation, and explored the potential of integrating single-date imaging data with multi-year in-situ measurements for mapping the spatial and temporal variation of ALT. Modeling results showed hyperspectral imaging was accurate for estimating ALT with a correlation coefficient (r) larger than 0.7, while application of WV-2 data produced an r around 0.4. Reasonable ALT patterns were generated, and the spatial and temporal variation of ALT was delineated between the shallowest (2015) and deepest (2019) years using hyperspectral data. This study suggests hyperspectral imaging is a promising tool for predicting field ALT measurements and monitoring ALT change at local scales. We expect this study will stimulate hyperspectral optical sensors for permafrost studies in general, and particularly for ALT upscaling.
format Article in Journal/Newspaper
author Caiyun Zhang
Thomas A. Douglas
John E. Anderson
author_facet Caiyun Zhang
Thomas A. Douglas
John E. Anderson
author_sort Caiyun Zhang
title Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
title_short Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
title_full Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
title_fullStr Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
title_full_unstemmed Modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
title_sort modeling and mapping permafrost active layer thickness using field measurements and remote sensing techniques
publisher Elsevier
publishDate 2021
url https://doi.org/10.1016/j.jag.2021.102455
https://doaj.org/article/f13ff21226f541369424fbf312bbbacc
genre Active layer thickness
permafrost
Alaska
genre_facet Active layer thickness
permafrost
Alaska
op_source International Journal of Applied Earth Observations and Geoinformation, Vol 102, Iss , Pp 102455- (2021)
op_relation 1569-8432
doi:10.1016/j.jag.2021.102455
https://doaj.org/article/f13ff21226f541369424fbf312bbbacc
op_rights undefined
op_doi https://doi.org/10.1016/j.jag.2021.102455
container_title International Journal of Applied Earth Observation and Geoinformation
container_volume 102
container_start_page 102455
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