The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula
Subarctic palsa mires undergo substantial transformation under climate impacts, and today a reliable marker of their degradation is the vegetation cover. We studied the correspondence between the surface traits of palsa degradation, as expressed in the vegetation composition, and the interior condit...
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ftdoajarticles:oai:doaj.org/article:c26db7f007d649088ffe21ef9ff8ccc6 2023-06-06T11:56:10+02:00 The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula Natalya Krutskikh Pavel Ryazantsev Pavel Ignashov Alexey Kabonen 2023-03-01T00:00:00Z https://doi.org/10.3390/rs15071896 https://doaj.org/article/c26db7f007d649088ffe21ef9ff8ccc6 EN eng MDPI AG https://www.mdpi.com/2072-4292/15/7/1896 https://doaj.org/toc/2072-4292 doi:10.3390/rs15071896 2072-4292 https://doaj.org/article/c26db7f007d649088ffe21ef9ff8ccc6 Remote Sensing, Vol 15, Iss 1896, p 1896 (2023) digital elevation model GPR cross-sections patterns machine learning land cover classification morphometric predictors Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15071896 2023-04-16T00:33:18Z Subarctic palsa mires undergo substantial transformation under climate impacts, and today a reliable marker of their degradation is the vegetation cover. We studied the correspondence between the surface traits of palsa degradation, as expressed in the vegetation composition, and the interior condition of permafrost within subarctic palsa mires in the central part of the Kola Peninsula. We have employed a set of methods to collect the data, including geobotanical relevés, unmanned aerial system (UAS) photogrammetry, and ground-penetrating radar (GPR) survey. Based on RGB orthophoto values and morphometric variables, we produced a land cover classification (LCC) consistent with the vegetation classes identified during field measurements. The outcome proves that the additional morphometric predictors improve the accuracy of classification algorithms. We identified three major patterns in GPR cross-sections defining (i) permafrost in palsas, (ii) water saturated peat, and (iii) the regular peat layer. As a result, our GPR data demonstrated a high correlation with land cover classes and pointed to some vegetation features controlled by the peat deposit inner structure. Under our results, palsas with thawing permafrost can be appraised using sequences of LCC. This is primarily the lichen hummock—tall shrub—carpet vegetation (LH–TSh–C) sequence from palsa top to foot. We have also detected an asymmetric configuration of permafrost in some palsas in the west-to-east direction and hypothesized that it can relate to the wind regime of the area and snow accumulation on the eastern slopes. Our results highlight that the combined application of the remote UAS photogrammetry and GPR survey enables a more precise delineation of the lateral degradation of palsas. Article in Journal/Newspaper kola peninsula palsa palsas permafrost Subarctic Directory of Open Access Journals: DOAJ Articles Kola Peninsula Remote Sensing 15 7 1896 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
digital elevation model GPR cross-sections patterns machine learning land cover classification morphometric predictors Science Q |
spellingShingle |
digital elevation model GPR cross-sections patterns machine learning land cover classification morphometric predictors Science Q Natalya Krutskikh Pavel Ryazantsev Pavel Ignashov Alexey Kabonen The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
topic_facet |
digital elevation model GPR cross-sections patterns machine learning land cover classification morphometric predictors Science Q |
description |
Subarctic palsa mires undergo substantial transformation under climate impacts, and today a reliable marker of their degradation is the vegetation cover. We studied the correspondence between the surface traits of palsa degradation, as expressed in the vegetation composition, and the interior condition of permafrost within subarctic palsa mires in the central part of the Kola Peninsula. We have employed a set of methods to collect the data, including geobotanical relevés, unmanned aerial system (UAS) photogrammetry, and ground-penetrating radar (GPR) survey. Based on RGB orthophoto values and morphometric variables, we produced a land cover classification (LCC) consistent with the vegetation classes identified during field measurements. The outcome proves that the additional morphometric predictors improve the accuracy of classification algorithms. We identified three major patterns in GPR cross-sections defining (i) permafrost in palsas, (ii) water saturated peat, and (iii) the regular peat layer. As a result, our GPR data demonstrated a high correlation with land cover classes and pointed to some vegetation features controlled by the peat deposit inner structure. Under our results, palsas with thawing permafrost can be appraised using sequences of LCC. This is primarily the lichen hummock—tall shrub—carpet vegetation (LH–TSh–C) sequence from palsa top to foot. We have also detected an asymmetric configuration of permafrost in some palsas in the west-to-east direction and hypothesized that it can relate to the wind regime of the area and snow accumulation on the eastern slopes. Our results highlight that the combined application of the remote UAS photogrammetry and GPR survey enables a more precise delineation of the lateral degradation of palsas. |
format |
Article in Journal/Newspaper |
author |
Natalya Krutskikh Pavel Ryazantsev Pavel Ignashov Alexey Kabonen |
author_facet |
Natalya Krutskikh Pavel Ryazantsev Pavel Ignashov Alexey Kabonen |
author_sort |
Natalya Krutskikh |
title |
The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
title_short |
The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
title_full |
The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
title_fullStr |
The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
title_full_unstemmed |
The Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula |
title_sort |
spatial analysis of vegetation cover and permafrost degradation for a subarctic palsa mire based on uas photogrammetry and gpr data in the kola peninsula |
publisher |
MDPI AG |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15071896 https://doaj.org/article/c26db7f007d649088ffe21ef9ff8ccc6 |
geographic |
Kola Peninsula |
geographic_facet |
Kola Peninsula |
genre |
kola peninsula palsa palsas permafrost Subarctic |
genre_facet |
kola peninsula palsa palsas permafrost Subarctic |
op_source |
Remote Sensing, Vol 15, Iss 1896, p 1896 (2023) |
op_relation |
https://www.mdpi.com/2072-4292/15/7/1896 https://doaj.org/toc/2072-4292 doi:10.3390/rs15071896 2072-4292 https://doaj.org/article/c26db7f007d649088ffe21ef9ff8ccc6 |
op_doi |
https://doi.org/10.3390/rs15071896 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
7 |
container_start_page |
1896 |
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1767963579135295488 |