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...
Published in: | Remote Sensing |
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Main Authors: | , , , , |
Other Authors: | , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2023
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Subjects: | |
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 |
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ftccsdartic:oai:HAL:hal-04002231v1 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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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 |
_version_ |
1782330976627589120 |
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 |