Kartläggning av den minskande palsen i Storflaket och uppskattning av dess markinlagrade kol samt metan utsläpp under de senaste sex decennierna (1960-2018)

During the last decades permafrost in the sub-Artic region has been experiencing large scale thawing due to the climate change the region has undergone. Palsa mires, elevated peat mounds with a frozen core, show permafrost degradation due to their sensitivity to climate change. This study examined the long-term degradation of the Storflaket palsa mire from 1960 to 2018 by examining landcover changes and their effects on soil organic carbon storage and methane emissions. This was achieved with orthophotos from 1960, 1994, 2002, 2008 and 2018, and two remote sensing techniques: manual digitization in ArcGIS and random forest classification in RStudio. Three landcover classes were used (Palsa, Fen and Open water) to capture the transition from permafrost-rich palsa vegetation to permafrost-free wetland vegetation. The method of manual digitization presented more realistic landcover classifications due to challenges in classifying historical, non-RGB images, and due to the discontinuous palsa extent that the RF resulted in. From 1960 to 2018 the palsa extent of Storflaket resulted in a total loss of 21%, with an increasing average annual degradation rate during the last three decades. The transition from palsa to fen resulted in an estimated remobilization of 438 tons of carbon and an ongoing increase in methane emissions during the last six decades. These estimates are associated with large uncertainties and more field data would be needed to better constrain this. This study highlights the importance of historical remote sensing in tracking permafrost landcover change and its wider climate feedback implications.

Publication Details

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DiVA at Umeå University (Umeå University)
Published
2025-01-01
Primary Topic
Magnetic confinement fusion research
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article
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article

Kartläggning av den minskande palsen i Storflaket och uppskattning av dess markinlagrade kol samt metan utsläpp under de senaste sex decennierna (1960-2018)

DiVA at Umeå University (Umeå University)
Magnetic confinement fusion research
article

Kartläggning av den minskande palsen i Storflaket och uppskattning av dess markinlagrade kol samt metan utsläpp under de senaste sex decennierna (1960-2018)

article en

Abstract

During the last decades permafrost in the sub-Artic region has been experiencing large scale thawing due to the climate change the region has undergone. Palsa mires, elevated peat mounds with a frozen core, show permafrost degradation due to their sensitivity to climate change. This study examined the long-term degradation of the Storflaket palsa mire from 1960 to 2018 by examining landcover changes and their effects on soil organic carbon storage and methane emissions. This was achieved with orthophotos from 1960, 1994, 2002, 2008 and 2018, and two remote sensing techniques: manual digitization in ArcGIS and random forest classification in RStudio. Three landcover classes were used (Palsa, Fen and Open water) to capture the transition from permafrost-rich palsa vegetation to permafrost-free wetland vegetation. The method of manual digitization presented more realistic landcover classifications due to challenges in classifying historical, non-RGB images, and due to the discontinuous palsa extent that the RF resulted in. From 1960 to 2018 the palsa extent of Storflaket resulted in a total loss of 21%, with an increasing average annual degradation rate during the last three decades. The transition from palsa to fen resulted in an estimated remobilization of 438 tons of carbon and an ongoing increase in methane emissions during the last six decades. These estimates are associated with large uncertainties and more field data would be needed to better constrain this. This study highlights the importance of historical remote sensing in tracking permafrost landcover change and its wider climate feedback implications.

DiVA at Umeå University (Umeå University)
Climate action
Openalex Percentile: Top 31%
Magnetic confinement fusion research
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