Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery

Changes in vegetation productivity based on normalized difference vegetation index (NDVI) have been reported from Arctic regions. Most studies use very coarse spatial resolution remote sensing data that cannot isolate landscape level factors. For example, on Yamal Peninsula in West Siberia enhanced...

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Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Mariana Verdonen, Logan T Berner, Bruce C Forbes, Timo Kumpula
Format: Article in Journal/Newspaper
Language:English
Published: IOP Publishing 2020
Subjects:
Q
Online Access:https://doi.org/10.1088/1748-9326/abb500
https://doaj.org/article/647a570933d44a859ac0f3b687fa495f
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spelling ftdoajarticles:oai:doaj.org/article:647a570933d44a859ac0f3b687fa495f 2023-09-05T13:16:56+02:00 Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery Mariana Verdonen Logan T Berner Bruce C Forbes Timo Kumpula 2020-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/abb500 https://doaj.org/article/647a570933d44a859ac0f3b687fa495f EN eng IOP Publishing https://doi.org/10.1088/1748-9326/abb500 https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/abb500 1748-9326 https://doaj.org/article/647a570933d44a859ac0f3b687fa495f Environmental Research Letters, Vol 15, Iss 10, p 105020 (2020) NDVI remote sensing Google Earth Engine Landsat tundra regeneration cryogenic landslides Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2020 ftdoajarticles https://doi.org/10.1088/1748-9326/abb500 2023-08-13T00:37:14Z Changes in vegetation productivity based on normalized difference vegetation index (NDVI) have been reported from Arctic regions. Most studies use very coarse spatial resolution remote sensing data that cannot isolate landscape level factors. For example, on Yamal Peninsula in West Siberia enhanced willow growth has been linked to widespread landslide activity, but the effect of landslides on regional NDVI dynamics is unknown. Here we apply a novel satellite-based NDVI analysis to investigate the vegetation regeneration patterns of active-layer detachments following a major landslide event in 1989. We analyzed time series data of Landsat and very high-resolution (VHR) imagery from QuickBird-2 and WorldView-2 and 3 characterizing a study area of ca. 35 km ^2 . Landsat revealed that natural regeneration of low Arctic tundra progressed rapidly during the first two decades after the landslide event. However, during the past decade, the difference between landslide shear surfaces and surrounding areas remained relatively unchanged despite the advance of vegetation succession. Time series also revealed that NDVI generally declined since 2013 within the study area. The VHR imagery allowed detection of NDVI change ‘hot-spots’ that included temporary degradation of vegetation cover, as well as new and expanding thaw slumps, which were too small to be detected from Landsat satellite data. Our study demonstrates that landslides can have pronounced and long-lasting impacts on tundra vegetation. Thermokarst landslides and associated impacts on vegetation will likely become increasingly common in NW Siberia and other Arctic regions with continued warming. Article in Journal/Newspaper Arctic Thermokarst Tundra Yamal Peninsula Siberia Directory of Open Access Journals: DOAJ Articles Arctic Yamal Peninsula ENVELOPE(69.873,69.873,70.816,70.816) Environmental Research Letters 15 10 105020
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic NDVI
remote sensing
Google Earth Engine
Landsat
tundra regeneration
cryogenic landslides
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
spellingShingle NDVI
remote sensing
Google Earth Engine
Landsat
tundra regeneration
cryogenic landslides
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
Mariana Verdonen
Logan T Berner
Bruce C Forbes
Timo Kumpula
Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
topic_facet NDVI
remote sensing
Google Earth Engine
Landsat
tundra regeneration
cryogenic landslides
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Science
Q
Physics
QC1-999
description Changes in vegetation productivity based on normalized difference vegetation index (NDVI) have been reported from Arctic regions. Most studies use very coarse spatial resolution remote sensing data that cannot isolate landscape level factors. For example, on Yamal Peninsula in West Siberia enhanced willow growth has been linked to widespread landslide activity, but the effect of landslides on regional NDVI dynamics is unknown. Here we apply a novel satellite-based NDVI analysis to investigate the vegetation regeneration patterns of active-layer detachments following a major landslide event in 1989. We analyzed time series data of Landsat and very high-resolution (VHR) imagery from QuickBird-2 and WorldView-2 and 3 characterizing a study area of ca. 35 km ^2 . Landsat revealed that natural regeneration of low Arctic tundra progressed rapidly during the first two decades after the landslide event. However, during the past decade, the difference between landslide shear surfaces and surrounding areas remained relatively unchanged despite the advance of vegetation succession. Time series also revealed that NDVI generally declined since 2013 within the study area. The VHR imagery allowed detection of NDVI change ‘hot-spots’ that included temporary degradation of vegetation cover, as well as new and expanding thaw slumps, which were too small to be detected from Landsat satellite data. Our study demonstrates that landslides can have pronounced and long-lasting impacts on tundra vegetation. Thermokarst landslides and associated impacts on vegetation will likely become increasingly common in NW Siberia and other Arctic regions with continued warming.
format Article in Journal/Newspaper
author Mariana Verdonen
Logan T Berner
Bruce C Forbes
Timo Kumpula
author_facet Mariana Verdonen
Logan T Berner
Bruce C Forbes
Timo Kumpula
author_sort Mariana Verdonen
title Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
title_short Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
title_full Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
title_fullStr Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
title_full_unstemmed Periglacial vegetation dynamics in Arctic Russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
title_sort periglacial vegetation dynamics in arctic russia: decadal analysis of tundra regeneration on landslides with time series satellite imagery
publisher IOP Publishing
publishDate 2020
url https://doi.org/10.1088/1748-9326/abb500
https://doaj.org/article/647a570933d44a859ac0f3b687fa495f
long_lat ENVELOPE(69.873,69.873,70.816,70.816)
geographic Arctic
Yamal Peninsula
geographic_facet Arctic
Yamal Peninsula
genre Arctic
Thermokarst
Tundra
Yamal Peninsula
Siberia
genre_facet Arctic
Thermokarst
Tundra
Yamal Peninsula
Siberia
op_source Environmental Research Letters, Vol 15, Iss 10, p 105020 (2020)
op_relation https://doi.org/10.1088/1748-9326/abb500
https://doaj.org/toc/1748-9326
doi:10.1088/1748-9326/abb500
1748-9326
https://doaj.org/article/647a570933d44a859ac0f3b687fa495f
op_doi https://doi.org/10.1088/1748-9326/abb500
container_title Environmental Research Letters
container_volume 15
container_issue 10
container_start_page 105020
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