Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)

International audience The current rate and magnitude of temperature rise in the Arctic are disproportionately high compared to global averages. Along with other natural and anthropogenic disturbances, this warming has caused widespread permafrost degradation and soil subsidence, resulting in the fo...

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Published in:Remote Sensing
Main Authors: Hughes-Allen, Lara, Bouchard, Frédéric, Séjourné, Antoine, Fougeron, Gabriel, Léger, Emmanuel
Other Authors: Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Géochrononologie Traceurs Archéométrie (GEOTRAC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Géosciences Paris Saclay (GEOPS), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre d'Etudes Nordiques (CEN), Université Laval Québec (ULaval), Université de Sherbrooke (UdeS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2023
Subjects:
L
F
A
Ice
Online Access:https://hal.science/hal-04002231
https://hal.science/hal-04002231/document
https://hal.science/hal-04002231/file/rs2023Hughes1226.pdf
https://doi.org/10.3390/rs15051226
id ftccsdartic:oai:HAL:hal-04002231v1
record_format openpolar
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 Hughes-Allen
L. Bouchard
F. Séjourné
A. Fougeron
Mask R-CNN remote sensing Yedoma permafrost thermokarst greenhouse gas emissions
L
Bouchard
F
Séjourné
A
Fougeron
Mask R-CNN
remote sensing
Yedoma permafrost
thermokarst
greenhouse gas emissions
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
spellingShingle Hughes-Allen
L. Bouchard
F. Séjourné
A. Fougeron
Mask R-CNN remote sensing Yedoma permafrost thermokarst greenhouse gas emissions
L
Bouchard
F
Séjourné
A
Fougeron
Mask R-CNN
remote sensing
Yedoma permafrost
thermokarst
greenhouse gas emissions
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
Hughes-Allen, Lara
Bouchard, Frédéric
Séjourné, Antoine
Fougeron, Gabriel
Léger, Emmanuel
Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
topic_facet Hughes-Allen
L. Bouchard
F. Séjourné
A. Fougeron
Mask R-CNN remote sensing Yedoma permafrost thermokarst greenhouse gas emissions
L
Bouchard
F
Séjourné
A
Fougeron
Mask R-CNN
remote sensing
Yedoma permafrost
thermokarst
greenhouse gas emissions
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
description International audience The current rate and magnitude of temperature rise in the Arctic are disproportionately high compared to global averages. Along with other natural and anthropogenic disturbances, this warming has caused widespread permafrost degradation and soil subsidence, resulting in the formation of thermokarst (thaw) lakes in areas of ice-rich permafrost. These lakes are hotspots of greenhouse gas emissions (CO2 and CH4), but with substantial spatial and temporal heterogeneity across Arctic and sub-Arctic regions. In Central Yakutia (Eastern Siberia, Russia), nearly half of the landscape has been affected by thermokarst processes since the early Holocene, resulting in the formation of more than 10,000 partly drained lake depressions (alas lakes). It is not yet clear how recent changes in temperature and precipitation will affect existing lakes and the formation of new thermokarst lakes. A multi-decadal remote sensing analysis of lake formation and development was conducted for two large study areas (~1200 km2 each) in Central Yakutia. Mask Region-Based Convolutional Neural Networks (R-CNN) instance segmentation was used to semi-automate lake detection in Satellite pour l’Observation de la Terre (SPOT) and declassified US military (CORONA) images (1967–2019). Using these techniques, we quantified changes in lake surface area for three different lake types (unconnected alas lake, connected alas lake, and recent thermokarst lake) since the 1960s. Our results indicate that unconnected alas lakes are the dominant lake type, both in the number of lakes and total surface area coverage. Unconnected alas lakes appear to be more susceptible to changes in precipitation compared to the other two lake types. The majority of recent thermokarst lakes form within 1 km of observable human disturbance and their surface area is directly related to air temperature increases. These results suggest that climate change and human disturbances are having a strong impact on the landscape and hydrology of Central Yakutia. ...
author2 Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE)
Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Géochrononologie Traceurs Archéométrie (GEOTRAC)
Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Géosciences Paris Saclay (GEOPS)
Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Centre d'Etudes Nordiques (CEN)
Université Laval Québec (ULaval)
Université de Sherbrooke (UdeS)
format Article in Journal/Newspaper
author Hughes-Allen, Lara
Bouchard, Frédéric
Séjourné, Antoine
Fougeron, Gabriel
Léger, Emmanuel
author_facet Hughes-Allen, Lara
Bouchard, Frédéric
Séjourné, Antoine
Fougeron, Gabriel
Léger, Emmanuel
author_sort Hughes-Allen, Lara
title Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
title_short Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
title_full Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
title_fullStr Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
title_full_unstemmed Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia)
title_sort automated identification of thermokarst lakes using machine learning in the ice-rich permafrost landscape of central yakutia (eastern siberia)
publisher HAL CCSD
publishDate 2023
url https://hal.science/hal-04002231
https://hal.science/hal-04002231/document
https://hal.science/hal-04002231/file/rs2023Hughes1226.pdf
https://doi.org/10.3390/rs15051226
long_lat ENVELOPE(-57.333,-57.333,-64.200,-64.200)
geographic Arctic
Bouchard
geographic_facet Arctic
Bouchard
genre Arctic
Climate change
Ice
permafrost
Thermokarst
Yakutia
Siberia
genre_facet Arctic
Climate change
Ice
permafrost
Thermokarst
Yakutia
Siberia
op_source ISSN: 2072-4292
Remote Sensing
https://hal.science/hal-04002231
Remote Sensing, 2023, 15 (5), pp.1226. ⟨10.3390/rs15051226⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.3390/rs15051226
hal-04002231
https://hal.science/hal-04002231
https://hal.science/hal-04002231/document
https://hal.science/hal-04002231/file/rs2023Hughes1226.pdf
doi:10.3390/rs15051226
op_rights info:eu-repo/semantics/OpenAccess
op_doi https://doi.org/10.3390/rs15051226
container_title Remote Sensing
container_volume 15
container_issue 5
container_start_page 1226
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spelling ftccsdartic:oai:HAL:hal-04002231v1 2023-11-12T04:12:26+01:00 Automated Identification of Thermokarst Lakes Using Machine Learning in the Ice-Rich Permafrost Landscape of Central Yakutia (Eastern Siberia) Hughes-Allen, Lara Bouchard, Frédéric Séjourné, Antoine Fougeron, Gabriel Léger, Emmanuel Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Géochrononologie Traceurs Archéométrie (GEOTRAC) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Géosciences Paris Saclay (GEOPS) Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) Centre d'Etudes Nordiques (CEN) Université Laval Québec (ULaval) Université de Sherbrooke (UdeS) 2023-03 https://hal.science/hal-04002231 https://hal.science/hal-04002231/document https://hal.science/hal-04002231/file/rs2023Hughes1226.pdf https://doi.org/10.3390/rs15051226 en eng HAL CCSD MDPI info:eu-repo/semantics/altIdentifier/doi/10.3390/rs15051226 hal-04002231 https://hal.science/hal-04002231 https://hal.science/hal-04002231/document https://hal.science/hal-04002231/file/rs2023Hughes1226.pdf doi:10.3390/rs15051226 info:eu-repo/semantics/OpenAccess ISSN: 2072-4292 Remote Sensing https://hal.science/hal-04002231 Remote Sensing, 2023, 15 (5), pp.1226. ⟨10.3390/rs15051226⟩ Hughes-Allen L. Bouchard F. Séjourné A. Fougeron Mask R-CNN remote sensing Yedoma permafrost thermokarst greenhouse gas emissions L Bouchard F Séjourné A Fougeron Mask R-CNN remote sensing Yedoma permafrost thermokarst greenhouse gas emissions [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2023 ftccsdartic https://doi.org/10.3390/rs15051226 2023-10-21T22:49:41Z International audience The current rate and magnitude of temperature rise in the Arctic are disproportionately high compared to global averages. Along with other natural and anthropogenic disturbances, this warming has caused widespread permafrost degradation and soil subsidence, resulting in the formation of thermokarst (thaw) lakes in areas of ice-rich permafrost. These lakes are hotspots of greenhouse gas emissions (CO2 and CH4), but with substantial spatial and temporal heterogeneity across Arctic and sub-Arctic regions. In Central Yakutia (Eastern Siberia, Russia), nearly half of the landscape has been affected by thermokarst processes since the early Holocene, resulting in the formation of more than 10,000 partly drained lake depressions (alas lakes). It is not yet clear how recent changes in temperature and precipitation will affect existing lakes and the formation of new thermokarst lakes. A multi-decadal remote sensing analysis of lake formation and development was conducted for two large study areas (~1200 km2 each) in Central Yakutia. Mask Region-Based Convolutional Neural Networks (R-CNN) instance segmentation was used to semi-automate lake detection in Satellite pour l’Observation de la Terre (SPOT) and declassified US military (CORONA) images (1967–2019). Using these techniques, we quantified changes in lake surface area for three different lake types (unconnected alas lake, connected alas lake, and recent thermokarst lake) since the 1960s. Our results indicate that unconnected alas lakes are the dominant lake type, both in the number of lakes and total surface area coverage. Unconnected alas lakes appear to be more susceptible to changes in precipitation compared to the other two lake types. The majority of recent thermokarst lakes form within 1 km of observable human disturbance and their surface area is directly related to air temperature increases. These results suggest that climate change and human disturbances are having a strong impact on the landscape and hydrology of Central Yakutia. ... Article in Journal/Newspaper Arctic Climate change Ice permafrost Thermokarst Yakutia Siberia Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Arctic Bouchard ENVELOPE(-57.333,-57.333,-64.200,-64.200) Remote Sensing 15 5 1226