Quantifying rapid permafrost thaw with computer vision and graph theory
With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. Permafrost, as a key element of the Arctic system, stores vast amounts of organic carbon that can be microbially decomposed into the greenhouse gases CO2 and CH4 upon thaw. Ext...
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ftawi:oai:epic.awi.de:56655 2024-09-15T18:11:22+00:00 Quantifying rapid permafrost thaw with computer vision and graph theory Rettelbach, Tabea Langer, Moritz Nitze, Ingmar Helm, Veit Freytag, J. C. Grosse, Guido 2022-05-25 application/pdf https://epic.awi.de/id/eprint/56655/ https://epic.awi.de/id/eprint/56655/1/rettelbach_poster_icrss_lps.pdf https://hdl.handle.net/10013/epic.0ed4834d-69a3-47b7-a636-b7992d5c24d8 unknown https://epic.awi.de/id/eprint/56655/1/rettelbach_poster_icrss_lps.pdf Rettelbach, T. , Langer, M. orcid:0000-0002-2704-3655 , Nitze, I. orcid:0000-0002-1165-6852 , Helm, V. orcid:0000-0001-7788-9328 , Freytag, J. C. and Grosse, G. orcid:0000-0001-5895-2141 (2022) Quantifying rapid permafrost thaw with computer vision and graph theory , ESA Living Planet Symposium, Bonn, Germany, 23 May 2022 - 27 May 2022 . hdl:10013/epic.0ed4834d-69a3-47b7-a636-b7992d5c24d8 EPIC3ESA Living Planet Symposium, Bonn, Germany, 2022-05-23-2022-05-27 Conference notRev 2022 ftawi 2024-06-24T04:28:46Z With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. Permafrost, as a key element of the Arctic system, stores vast amounts of organic carbon that can be microbially decomposed into the greenhouse gases CO2 and CH4 upon thaw. Extensive thawing of these permafrost soils therefore has potentially substantial consequences to greenhouse gas concentrations in the atmosphere. In addition, thaw of ice-rich permafrost lastingly alters the surface topography and thus the hydrology. Fires represent an important disturbance in boreal permafrost regions and increasingly also in tundra regions as they combust the vegetation and upper organic soil layers that usually provide protective insulation to the permafrost below. Field studies and local remote sensing studies suggest that fire disturbances may trigger rapid permafrost thaw, with consequences often already observable in the first years post-disturbance. In polygonal ice-wedge landscapes, this becomes most prevalent through melting ice wedges and degrading troughs. The further these ice wedges degrade; the more troughs will likely connect and build an extensive hydrological network with changing patterns and degrees of connectivity that influences hydrology and runoff throughout large regions. While subsiding troughs over melting ice wedges may host new ponds, an increasing connectivity may also subsequently lead to more drainage of ponds, which in turn can limit further thaw and help stabilize the landscape. Whereas fire disturbances may accelerate the initiation of this process, the general warming of permafrost observed across the Arctic will eventually result in widespread degradation of polygonal landscapes. To quantify the changes in such dynamic landscapes over large regions, remote sensing data offers a valuable resource. However, considering the vast and ever-growing volumes of Earth observation data available, highly automated methods are needed that allow extracting information on the ... Conference Object Ice permafrost Tundra wedge* Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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ftawi |
language |
unknown |
description |
With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. Permafrost, as a key element of the Arctic system, stores vast amounts of organic carbon that can be microbially decomposed into the greenhouse gases CO2 and CH4 upon thaw. Extensive thawing of these permafrost soils therefore has potentially substantial consequences to greenhouse gas concentrations in the atmosphere. In addition, thaw of ice-rich permafrost lastingly alters the surface topography and thus the hydrology. Fires represent an important disturbance in boreal permafrost regions and increasingly also in tundra regions as they combust the vegetation and upper organic soil layers that usually provide protective insulation to the permafrost below. Field studies and local remote sensing studies suggest that fire disturbances may trigger rapid permafrost thaw, with consequences often already observable in the first years post-disturbance. In polygonal ice-wedge landscapes, this becomes most prevalent through melting ice wedges and degrading troughs. The further these ice wedges degrade; the more troughs will likely connect and build an extensive hydrological network with changing patterns and degrees of connectivity that influences hydrology and runoff throughout large regions. While subsiding troughs over melting ice wedges may host new ponds, an increasing connectivity may also subsequently lead to more drainage of ponds, which in turn can limit further thaw and help stabilize the landscape. Whereas fire disturbances may accelerate the initiation of this process, the general warming of permafrost observed across the Arctic will eventually result in widespread degradation of polygonal landscapes. To quantify the changes in such dynamic landscapes over large regions, remote sensing data offers a valuable resource. However, considering the vast and ever-growing volumes of Earth observation data available, highly automated methods are needed that allow extracting information on the ... |
format |
Conference Object |
author |
Rettelbach, Tabea Langer, Moritz Nitze, Ingmar Helm, Veit Freytag, J. C. Grosse, Guido |
spellingShingle |
Rettelbach, Tabea Langer, Moritz Nitze, Ingmar Helm, Veit Freytag, J. C. Grosse, Guido Quantifying rapid permafrost thaw with computer vision and graph theory |
author_facet |
Rettelbach, Tabea Langer, Moritz Nitze, Ingmar Helm, Veit Freytag, J. C. Grosse, Guido |
author_sort |
Rettelbach, Tabea |
title |
Quantifying rapid permafrost thaw with computer vision and graph theory |
title_short |
Quantifying rapid permafrost thaw with computer vision and graph theory |
title_full |
Quantifying rapid permafrost thaw with computer vision and graph theory |
title_fullStr |
Quantifying rapid permafrost thaw with computer vision and graph theory |
title_full_unstemmed |
Quantifying rapid permafrost thaw with computer vision and graph theory |
title_sort |
quantifying rapid permafrost thaw with computer vision and graph theory |
publishDate |
2022 |
url |
https://epic.awi.de/id/eprint/56655/ https://epic.awi.de/id/eprint/56655/1/rettelbach_poster_icrss_lps.pdf https://hdl.handle.net/10013/epic.0ed4834d-69a3-47b7-a636-b7992d5c24d8 |
genre |
Ice permafrost Tundra wedge* |
genre_facet |
Ice permafrost Tundra wedge* |
op_source |
EPIC3ESA Living Planet Symposium, Bonn, Germany, 2022-05-23-2022-05-27 |
op_relation |
https://epic.awi.de/id/eprint/56655/1/rettelbach_poster_icrss_lps.pdf Rettelbach, T. , Langer, M. orcid:0000-0002-2704-3655 , Nitze, I. orcid:0000-0002-1165-6852 , Helm, V. orcid:0000-0001-7788-9328 , Freytag, J. C. and Grosse, G. orcid:0000-0001-5895-2141 (2022) Quantifying rapid permafrost thaw with computer vision and graph theory , ESA Living Planet Symposium, Bonn, Germany, 23 May 2022 - 27 May 2022 . hdl:10013/epic.0ed4834d-69a3-47b7-a636-b7992d5c24d8 |
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1810448952676319232 |