Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data

International audience Permafrost landscapes are one of the most sensitive ecosystems that humans inhabit. Geocryological conditions determined by the presence of ice content, the genetic type of sediments, and the active layer are one of the most important variables for classifying the vulnerabilit...

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Main Authors: Gadal, Sébastien, Zakharov, Moisei, Kamicaityte, Jurate
Other Authors: Aix Marseille Université (AMU), 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), North-Eastern Federal University, Kaunas University of Technology (KTU), European Space Agency, CNES TOSCA TRISHNA (Cryosphere), FMSH-RBSF OSAMA (development Of an optimal human Security Model for The Arctic)
Format: Conference Object
Language:English
Published: HAL CCSD 2022
Subjects:
GIS
Ice
Online Access:https://hal.science/hal-03678952
https://hal.science/hal-03678952/document
https://hal.science/hal-03678952/file/Poster_LPS_2022.pdf
id ftunivnantes:oai:HAL:hal-03678952v1
record_format openpolar
institution Open Polar
collection Université de Nantes: HAL-UNIV-NANTES
op_collection_id ftunivnantes
language English
topic Permafrost landscape
Cryogenic processes
Arctic mountains
Remote sensing
Machine learning
GIS
Data fusion
Mapping
Complex indicators
Landscape classification
Thermal imagery
Sentinel 2 MSI
North-Eastern Siberia
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
spellingShingle Permafrost landscape
Cryogenic processes
Arctic mountains
Remote sensing
Machine learning
GIS
Data fusion
Mapping
Complex indicators
Landscape classification
Thermal imagery
Sentinel 2 MSI
North-Eastern Siberia
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Gadal, Sébastien
Zakharov, Moisei
Kamicaityte, Jurate
Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
topic_facet Permafrost landscape
Cryogenic processes
Arctic mountains
Remote sensing
Machine learning
GIS
Data fusion
Mapping
Complex indicators
Landscape classification
Thermal imagery
Sentinel 2 MSI
North-Eastern Siberia
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.ES]Environmental Sciences/Environmental and Society
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
description International audience Permafrost landscapes are one of the most sensitive ecosystems that humans inhabit. Geocryological conditions determined by the presence of ice content, the genetic type of sediments, and the active layer are one of the most important variables for classifying the vulnerability of an ecosystem to disturbances in vegetation and soil cover. These variables indicate cryogenic processes that can be activated during the degradation of permafrost. Cryogenic mapping is an important parameter for assessing the state of permafrost and infrastructure design in permafrost landscapes. However, the methods of remote sensing spatial modelling for understanding the distribution of cryogenic processes in the Arctic Siberian mountainous areas with continuous permafrost are still insufficient. The cartographies at the regional scales of 1:500 000 are inexistent. We need for permafrost landscape maps is increasing with the development of the North-East Siberian Arctic for the infrastructures and urban centres' risk assessments. Orulgan Ridge in North-East Siberia is one of these territories. This study examines the Orulgan Ridge region, as a case area, where we developed maps of the distribution of cryogenic processes based on the detailed landscape structure (including classification of environmental variables, vegetation covers and genetic type of sediments) with time-series Sentinel 2 MSI and Landsat 8 OLI, and stereogrammetric digital elevation model of the ArcticDEM data. The combination of Random Forest classifier and geomorphological GIS terrain analysis has successfully distinguished 6 classes of boreal mountain taiga and 3 classes of arctic tundra and mountain desert. Based on the indicator parameters of the interrelation of ecological variables (such as vegetation and topographic position) adopted in permafrost-landscape cartography, we carried out the regionalization of cryogenic processes. We made a classification of the genetic type of deposits, which determines the likelihood of the ...
author2 Aix Marseille Université (AMU)
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)
North-Eastern Federal University
Kaunas University of Technology (KTU)
European Space Agency
CNES TOSCA TRISHNA (Cryosphere)
FMSH-RBSF OSAMA (development Of an optimal human Security Model for The Arctic)
format Conference Object
author Gadal, Sébastien
Zakharov, Moisei
Kamicaityte, Jurate
author_facet Gadal, Sébastien
Zakharov, Moisei
Kamicaityte, Jurate
author_sort Gadal, Sébastien
title Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
title_short Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
title_full Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
title_fullStr Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
title_full_unstemmed Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data
title_sort mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the north-east arctic siberian taiga and tundra from landsat 8, sentinel 2, and dem data
publisher HAL CCSD
publishDate 2022
url https://hal.science/hal-03678952
https://hal.science/hal-03678952/document
https://hal.science/hal-03678952/file/Poster_LPS_2022.pdf
op_coverage Bonn, Germany
geographic Arctic
geographic_facet Arctic
genre Arctic
Ice
permafrost
taiga
Tundra
Siberia
genre_facet Arctic
Ice
permafrost
taiga
Tundra
Siberia
op_source ESA Living Planet Symposium 2022
https://hal.science/hal-03678952
ESA Living Planet Symposium 2022, May 2022, Bonn, Germany. , 2022
https://express.converia.de/frontend/index.php?page_id=18446&v=List&do=15&day=3995&ses=20699#
op_relation hal-03678952
https://hal.science/hal-03678952
https://hal.science/hal-03678952/document
https://hal.science/hal-03678952/file/Poster_LPS_2022.pdf
op_rights info:eu-repo/semantics/OpenAccess
_version_ 1766323667401179136
spelling ftunivnantes:oai:HAL:hal-03678952v1 2023-05-15T14:52:25+02:00 Mapping cryogenic processes and assessing the sustainability of permafrost landscapes in the North-East Arctic Siberian taiga and tundra from Landsat 8, Sentinel 2, and DEM data Gadal, Sébastien Zakharov, Moisei Kamicaityte, Jurate Aix Marseille Université (AMU) 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) North-Eastern Federal University Kaunas University of Technology (KTU) European Space Agency CNES TOSCA TRISHNA (Cryosphere) FMSH-RBSF OSAMA (development Of an optimal human Security Model for The Arctic) Bonn, Germany 2022-05-23 https://hal.science/hal-03678952 https://hal.science/hal-03678952/document https://hal.science/hal-03678952/file/Poster_LPS_2022.pdf en eng HAL CCSD hal-03678952 https://hal.science/hal-03678952 https://hal.science/hal-03678952/document https://hal.science/hal-03678952/file/Poster_LPS_2022.pdf info:eu-repo/semantics/OpenAccess ESA Living Planet Symposium 2022 https://hal.science/hal-03678952 ESA Living Planet Symposium 2022, May 2022, Bonn, Germany. , 2022 https://express.converia.de/frontend/index.php?page_id=18446&v=List&do=15&day=3995&ses=20699# Permafrost landscape Cryogenic processes Arctic mountains Remote sensing Machine learning GIS Data fusion Mapping Complex indicators Landscape classification Thermal imagery Sentinel 2 MSI North-Eastern Siberia [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation [SHS.GEO]Humanities and Social Sciences/Geography [SDE.ES]Environmental Sciences/Environmental and Society [SHS.STAT]Humanities and Social Sciences/Methods and statistics [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] info:eu-repo/semantics/conferenceObject Conference poster 2022 ftunivnantes 2023-02-01T00:16:16Z International audience Permafrost landscapes are one of the most sensitive ecosystems that humans inhabit. Geocryological conditions determined by the presence of ice content, the genetic type of sediments, and the active layer are one of the most important variables for classifying the vulnerability of an ecosystem to disturbances in vegetation and soil cover. These variables indicate cryogenic processes that can be activated during the degradation of permafrost. Cryogenic mapping is an important parameter for assessing the state of permafrost and infrastructure design in permafrost landscapes. However, the methods of remote sensing spatial modelling for understanding the distribution of cryogenic processes in the Arctic Siberian mountainous areas with continuous permafrost are still insufficient. The cartographies at the regional scales of 1:500 000 are inexistent. We need for permafrost landscape maps is increasing with the development of the North-East Siberian Arctic for the infrastructures and urban centres' risk assessments. Orulgan Ridge in North-East Siberia is one of these territories. This study examines the Orulgan Ridge region, as a case area, where we developed maps of the distribution of cryogenic processes based on the detailed landscape structure (including classification of environmental variables, vegetation covers and genetic type of sediments) with time-series Sentinel 2 MSI and Landsat 8 OLI, and stereogrammetric digital elevation model of the ArcticDEM data. The combination of Random Forest classifier and geomorphological GIS terrain analysis has successfully distinguished 6 classes of boreal mountain taiga and 3 classes of arctic tundra and mountain desert. Based on the indicator parameters of the interrelation of ecological variables (such as vegetation and topographic position) adopted in permafrost-landscape cartography, we carried out the regionalization of cryogenic processes. We made a classification of the genetic type of deposits, which determines the likelihood of the ... Conference Object Arctic Ice permafrost taiga Tundra Siberia Université de Nantes: HAL-UNIV-NANTES Arctic