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...
Published in: | IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium |
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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 |
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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 |
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