Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes

International audience Shifting landscape boundaries is one of the long-term consequences of climate change. The transitional ecosystems between the arctic tundra and boreal forests in the mountains are open systems for the impact of climate change. The spread of continuous permafrost in these lands...

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Main Authors: Gadal, Sébastien, Zakharov, Moisei
Other Authors: North-Eastern Federal University, Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Aix Marseille Université (AMU), CNES TOSCA TRISHNA (Cryosphere), CNES, ISRO
Format: Conference Object
Language:English
Published: HAL CCSD 2022
Subjects:
Online Access:https://hal.science/hal-03622131
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spelling ftccsdartic:oai:HAL:hal-03622131v1 2023-05-15T14:59:09+02:00 Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes Gadal, Sébastien Zakharov, Moisei North-Eastern Federal University Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE) Université Nice Sophia Antipolis (1965 - 2019) (UNS) COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA) Aix Marseille Université (AMU) CNES TOSCA TRISHNA (Cryosphere) CNES ISRO Toulouse, France 2022-03-22 https://hal.science/hal-03622131 en eng HAL CCSD hal-03622131 https://hal.science/hal-03622131 http://creativecommons.org/licenses/by-nc/ CC-BY-NC TRISHNA Days 2022 https://hal.science/hal-03622131 TRISHNA Days 2022, CNES; ISRO, Mar 2022, Toulouse, France https://www.trishnadays.com Permasfrost landscapes Thermal remote sensing Big data image processing Machine learning Land surface temperature Landsat 8 TIRS Arctic mountains Siberia Yakutia [SHS.STAT]Humanities and Social Sciences/Methods and statistics [SDE.ES]Environmental Sciences/Environmental and Society [SHS.GEO]Humanities and Social Sciences/Geography [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] info:eu-repo/semantics/conferenceObject Conference papers 2022 ftccsdartic 2023-02-12T14:46:38Z International audience Shifting landscape boundaries is one of the long-term consequences of climate change. The transitional ecosystems between the arctic tundra and boreal forests in the mountains are open systems for the impact of climate change. The spread of continuous permafrost in these landscapes also accelerates the response of the ecosystem to climatic fluctuations. Thus, the bio productivity and boundaries of permafrost landscapes change in accordance with the dynamics of energy supply and humidity. This study presents the results of modelling the dynamics of the transitional permafrost landscapes between tundra and boreal forests of the Orulgan ridge in North-East Siberia. The modelling is based on the integration of Landsat 7 and 8 thermal infrared images. The methodology used is based on the analysis of mountain tundra areas with climatic characteristics close to boreal landscapes according to long-term data from WorldClim. These data show a positive trend in mean temperature and a negative trend in total precipitation. The distribution of landscape types on the territory of the ridge is associated with relief, which determines the contrast of climatic conditions on a local scale. The Land Surface Temperature (LST) extracted from thermal remote sensing data is a critical parameter in assessing the energy balance of mountain permafrost landscapes at the local level. Therefore, in the selected test area, we analysed the correlation between the land cover change from 1999 to 2020 with the extracted LST from Landsat 7 ETM+ and 8 TIRS thermal images. We found that the advance of forests on the tundra most often occurs on the slopes of the southern exposure with a significant increase in LST and a gentle slope of diluvial deposits and solifluction. Thus, we have determined the possibilities of using thermal images in assessing the impact of climate change in the Arctic mountainous territories of the permafrost zone with natural landscape dynamics, with a low intensity of anthropogenic impact and in ... Conference Object Arctic Climate change permafrost Tundra Yakutia Siberia Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Arctic
institution Open Polar
collection Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
op_collection_id ftccsdartic
language English
topic Permasfrost landscapes
Thermal remote sensing
Big data image processing
Machine learning
Land surface temperature
Landsat 8 TIRS
Arctic mountains
Siberia
Yakutia
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.GEO]Humanities and Social Sciences/Geography
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
spellingShingle Permasfrost landscapes
Thermal remote sensing
Big data image processing
Machine learning
Land surface temperature
Landsat 8 TIRS
Arctic mountains
Siberia
Yakutia
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.GEO]Humanities and Social Sciences/Geography
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Gadal, Sébastien
Zakharov, Moisei
Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
topic_facet Permasfrost landscapes
Thermal remote sensing
Big data image processing
Machine learning
Land surface temperature
Landsat 8 TIRS
Arctic mountains
Siberia
Yakutia
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.GEO]Humanities and Social Sciences/Geography
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
description International audience Shifting landscape boundaries is one of the long-term consequences of climate change. The transitional ecosystems between the arctic tundra and boreal forests in the mountains are open systems for the impact of climate change. The spread of continuous permafrost in these landscapes also accelerates the response of the ecosystem to climatic fluctuations. Thus, the bio productivity and boundaries of permafrost landscapes change in accordance with the dynamics of energy supply and humidity. This study presents the results of modelling the dynamics of the transitional permafrost landscapes between tundra and boreal forests of the Orulgan ridge in North-East Siberia. The modelling is based on the integration of Landsat 7 and 8 thermal infrared images. The methodology used is based on the analysis of mountain tundra areas with climatic characteristics close to boreal landscapes according to long-term data from WorldClim. These data show a positive trend in mean temperature and a negative trend in total precipitation. The distribution of landscape types on the territory of the ridge is associated with relief, which determines the contrast of climatic conditions on a local scale. The Land Surface Temperature (LST) extracted from thermal remote sensing data is a critical parameter in assessing the energy balance of mountain permafrost landscapes at the local level. Therefore, in the selected test area, we analysed the correlation between the land cover change from 1999 to 2020 with the extracted LST from Landsat 7 ETM+ and 8 TIRS thermal images. We found that the advance of forests on the tundra most often occurs on the slopes of the southern exposure with a significant increase in LST and a gentle slope of diluvial deposits and solifluction. Thus, we have determined the possibilities of using thermal images in assessing the impact of climate change in the Arctic mountainous territories of the permafrost zone with natural landscape dynamics, with a low intensity of anthropogenic impact and in ...
author2 North-Eastern Federal University
Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE)
Université Nice Sophia Antipolis (1965 - 2019) (UNS)
COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
Aix Marseille Université (AMU)
CNES TOSCA TRISHNA (Cryosphere)
CNES
ISRO
format Conference Object
author Gadal, Sébastien
Zakharov, Moisei
author_facet Gadal, Sébastien
Zakharov, Moisei
author_sort Gadal, Sébastien
title Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
title_short Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
title_full Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
title_fullStr Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
title_full_unstemmed Landsat thermal images to estimate the dynamics of northeast Siberian mountain permafrost landscapes
title_sort landsat thermal images to estimate the dynamics of northeast siberian mountain permafrost landscapes
publisher HAL CCSD
publishDate 2022
url https://hal.science/hal-03622131
op_coverage Toulouse, France
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
permafrost
Tundra
Yakutia
Siberia
genre_facet Arctic
Climate change
permafrost
Tundra
Yakutia
Siberia
op_source TRISHNA Days 2022
https://hal.science/hal-03622131
TRISHNA Days 2022, CNES; ISRO, Mar 2022, Toulouse, France
https://www.trishnadays.com
op_relation hal-03622131
https://hal.science/hal-03622131
op_rights http://creativecommons.org/licenses/by-nc/
op_rightsnorm CC-BY-NC
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