Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery

International audience In recent years, the accumulation of cloud-free remote sensing thermal infrared data for high-latitude permafrost regions makes it possible to use them to identify active cryogenic land surface processes (ACP) spurred by climate change and human activities. ACP is an extremely...

Full description

Bibliographic Details
Published in:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Main Authors: Gadal, Sébastien, Zakharov, Moisei
Other Authors: Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE), Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), North-Eastern Federal University, CNES TOSCA THRISNA, IEEE
Format: Conference Object
Language:English
Published: HAL CCSD 2023
Subjects:
Online Access:https://hal.science/hal-04254737
https://hal.science/hal-04254737/document
https://hal.science/hal-04254737/file/Cryogenic_Land_Surface_Process_Detection.pdf
https://doi.org/10.1109/IGARSS52108.2023.10282807
id ftccsdartic:oai:HAL:hal-04254737v1
record_format openpolar
spelling ftccsdartic:oai:HAL:hal-04254737v1 2023-11-12T04:24:30+01:00 Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery Gadal, Sébastien Zakharov, Moisei Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE) Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA) North-Eastern Federal University CNES TOSCA THRISNA IEEE Pasadena, CA, United States 2023-07-16 https://hal.science/hal-04254737 https://hal.science/hal-04254737/document https://hal.science/hal-04254737/file/Cryogenic_Land_Surface_Process_Detection.pdf https://doi.org/10.1109/IGARSS52108.2023.10282807 en eng HAL CCSD IEEE info:eu-repo/semantics/altIdentifier/doi/10.1109/IGARSS52108.2023.10282807 hal-04254737 https://hal.science/hal-04254737 https://hal.science/hal-04254737/document https://hal.science/hal-04254737/file/Cryogenic_Land_Surface_Process_Detection.pdf doi:10.1109/IGARSS52108.2023.10282807 http://creativecommons.org/licenses/by-nd/ 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023) https://hal.science/hal-04254737 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023), IEEE, Jul 2023, Pasadena, CA, United States. pp.237-240, ⟨10.1109/IGARSS52108.2023.10282807⟩ https://2023.ieeeigarss.org/ land surface temperature split-window algorithm thermal anomaly land surface cryogenic process Landsa [SHS.GEO]Humanities and Social Sciences/Geography [SDE.IE]Environmental Sciences/Environmental Engineering [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing info:eu-repo/semantics/conferenceObject Conference papers 2023 ftccsdartic https://doi.org/10.1109/IGARSS52108.2023.10282807 2023-10-28T22:29:38Z International audience In recent years, the accumulation of cloud-free remote sensing thermal infrared data for high-latitude permafrost regions makes it possible to use them to identify active cryogenic land surface processes (ACP) spurred by climate change and human activities. ACP is an extremely important indicator of excitations in the energy cycle of permafrost landscapes and changes in the carbon budget. In this paper, we test the time series of land surface temperature (LST) extracted from Landsat 8 OLI/TIRS datasets using a split window algorithm (SWA) to identify ACP for the study area in the mountains of Northeastern Siberia. We identified active cryogenic processes from thermal anomalies detected using standard deviation thresholds on 5 datasets for selected dates. Our results show that multi-year verified high resolution LST data for the second half of the summer period can be applicable for identifying an area with active cryogenic processes in the valley and disturbed permafrost landscapes, provided they can indicate the local effects of processes associated with drainage degradation and vegetation change. Conference Object permafrost Siberia Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium 237 240
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 land surface temperature
split-window algorithm
thermal anomaly
land surface cryogenic process
Landsa
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.IE]Environmental Sciences/Environmental Engineering
[SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
spellingShingle land surface temperature
split-window algorithm
thermal anomaly
land surface cryogenic process
Landsa
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.IE]Environmental Sciences/Environmental Engineering
[SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Gadal, Sébastien
Zakharov, Moisei
Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
topic_facet land surface temperature
split-window algorithm
thermal anomaly
land surface cryogenic process
Landsa
[SHS.GEO]Humanities and Social Sciences/Geography
[SDE.IE]Environmental Sciences/Environmental Engineering
[SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
description International audience In recent years, the accumulation of cloud-free remote sensing thermal infrared data for high-latitude permafrost regions makes it possible to use them to identify active cryogenic land surface processes (ACP) spurred by climate change and human activities. ACP is an extremely important indicator of excitations in the energy cycle of permafrost landscapes and changes in the carbon budget. In this paper, we test the time series of land surface temperature (LST) extracted from Landsat 8 OLI/TIRS datasets using a split window algorithm (SWA) to identify ACP for the study area in the mountains of Northeastern Siberia. We identified active cryogenic processes from thermal anomalies detected using standard deviation thresholds on 5 datasets for selected dates. Our results show that multi-year verified high resolution LST data for the second half of the summer period can be applicable for identifying an area with active cryogenic processes in the valley and disturbed permafrost landscapes, provided they can indicate the local effects of processes associated with drainage degradation and vegetation change.
author2 Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE)
Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
North-Eastern Federal University
CNES TOSCA THRISNA
IEEE
format Conference Object
author Gadal, Sébastien
Zakharov, Moisei
author_facet Gadal, Sébastien
Zakharov, Moisei
author_sort Gadal, Sébastien
title Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
title_short Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
title_full Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
title_fullStr Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
title_full_unstemmed Cryogenic Land Surface Process Detection in Siberian High Latitude Mountain Permafrost Landscape by Time Series Landsat Thermal Imagery
title_sort cryogenic land surface process detection in siberian high latitude mountain permafrost landscape by time series landsat thermal imagery
publisher HAL CCSD
publishDate 2023
url https://hal.science/hal-04254737
https://hal.science/hal-04254737/document
https://hal.science/hal-04254737/file/Cryogenic_Land_Surface_Process_Detection.pdf
https://doi.org/10.1109/IGARSS52108.2023.10282807
op_coverage Pasadena, CA, United States
genre permafrost
Siberia
genre_facet permafrost
Siberia
op_source 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023)
https://hal.science/hal-04254737
2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023), IEEE, Jul 2023, Pasadena, CA, United States. pp.237-240, ⟨10.1109/IGARSS52108.2023.10282807⟩
https://2023.ieeeigarss.org/
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1109/IGARSS52108.2023.10282807
hal-04254737
https://hal.science/hal-04254737
https://hal.science/hal-04254737/document
https://hal.science/hal-04254737/file/Cryogenic_Land_Surface_Process_Detection.pdf
doi:10.1109/IGARSS52108.2023.10282807
op_rights http://creativecommons.org/licenses/by-nd/
op_doi https://doi.org/10.1109/IGARSS52108.2023.10282807
container_title IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
container_start_page 237
op_container_end_page 240
_version_ 1782338979874471936