Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

ABSTRACT Maximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R 2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.

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Publication Details

Journal
Permafrost and Periglacial Processes
Published
2024-09-17
DOI
https://doi.org/10.1002/ppp.2252
Citations
4
Primary Topic
Climate change and permafrost
Type
article
Field-Weighted Citation Impact
1.51

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article

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

Miguel Villoslada, Teemu Tahvanainen, Tiina H. M. Kolari, Timo Kumpula et al.
4 citations
Permafrost and Periglacial Processes
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article

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

Miguel Villoslada, Teemu Tahvanainen, Tiina H. M. Kolari, Timo Kumpula, Pasi Korpelainen, Paolo Tarolli, Mariana Verdonen
article en
4 citations

Abstract

ABSTRACT Maximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R 2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.

Permafrost and Periglacial ProcessesVol. 36(1)
Agricultural University of Iceland (IS), University of Padua (IT), Université du Québec à Montréal (CA), University of Eastern Finland (FI), Estonian University of Life Sciences (EE)
Suomalainen Tiedeakatemia, Suomen Kulttuurirahasto, Ympäristöministeriö, Erasmus+
Openalex Percentile: Top 19%
Climate change and permafrost
1.51
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