A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes

In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-w...

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Published in:Remote Sensing
Main Authors: Rettelbach, Tabea, Langer, Moritz (Dr.), Nitze, Ingmar, Jones, Benjamin, Helm, Veit, Freytag, Johann-Christoph, Grosse, Guido (Prof. Dr.)
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://publishup.uni-potsdam.de/frontdoor/index/index/docId/66045
https://doi.org/10.3390/rs13163098
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author Rettelbach, Tabea
Langer, Moritz (Dr.)
Nitze, Ingmar
Jones, Benjamin
Helm, Veit
Freytag, Johann-Christoph
Grosse, Guido (Prof. Dr.)
author_facet Rettelbach, Tabea
Langer, Moritz (Dr.)
Nitze, Ingmar
Jones, Benjamin
Helm, Veit
Freytag, Johann-Christoph
Grosse, Guido (Prof. Dr.)
author_sort Rettelbach, Tabea
collection University of Potsdam: publish.UP
container_issue 16
container_start_page 3098
container_title Remote Sensing
container_volume 13
description In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-wedge polygons. This process has important implications for surface hydrology, as the connectivity of such troughs determines the rate of drainage for these lowland landscapes. In this study, we present a comprehensive, modular, and highly automated workflow to extract, to represent, and to analyze remotely sensed ice-wedge polygonal trough networks as a graph (i.e., network structure). With computer vision methods, we efficiently extract the trough locations as well as their geomorphometric information on trough depth and width from high-resolution digital elevation models and link these data within the graph. Further, we present and discuss the benefits of graph analysis algorithms for characterizing the erosional development of such thaw-affected landscapes. Based on our graph analysis, we show how thaw subsidence has progressed between 2009 and 2019 following burning at the Anaktuvuk River fire scar in northern Alaska, USA. We observed a considerable increase in the number of discernible troughs within the study area, while simultaneously the number of disconnected networks decreased from 54 small networks in 2009 to only six considerably larger disconnected networks in 2019. On average, the width of the troughs has increased by 13.86%, while the average depth has slightly decreased by 10.31%. Overall, our new automated approach allows for monitoring ice-wedge dynamics in unprecedented spatial detail, while simultaneously reducing the data to quantifiable geometric measures and spatial relationships.
format Article in Journal/Newspaper
genre Arctic
Ice
permafrost
wedge*
Alaska
genre_facet Arctic
Ice
permafrost
wedge*
Alaska
geographic Arctic
geographic_facet Arctic
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institution Open Polar
language English
op_collection_id ftubpotsdam
op_doi https://doi.org/10.3390/rs13163098
op_relation https://doi.org/10.3390/rs13163098
op_rights https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/closedAccess
publishDate 2021
record_format openpolar
spelling ftubpotsdam:oai:kobv.de-opus4-uni-potsdam:66045 2025-05-11T14:16:34+00:00 A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes Rettelbach, Tabea Langer, Moritz (Dr.) Nitze, Ingmar Jones, Benjamin Helm, Veit Freytag, Johann-Christoph Grosse, Guido (Prof. Dr.) 2021-08-05 https://publishup.uni-potsdam.de/frontdoor/index/index/docId/66045 https://doi.org/10.3390/rs13163098 eng eng https://doi.org/10.3390/rs13163098 https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/closedAccess ddc:620 Institut für Geowissenschaften article doc-type:article 2021 ftubpotsdam https://doi.org/10.3390/rs13163098 2025-04-15T14:28:14Z In response to increasing Arctic temperatures, ice-rich permafrost landscapes are undergoing rapid changes. In permafrost lowlands, polygonal ice wedges are especially prone to degradation. Melting of ice wedges results in deepening troughs and the transition from low-centered to high-centered ice-wedge polygons. This process has important implications for surface hydrology, as the connectivity of such troughs determines the rate of drainage for these lowland landscapes. In this study, we present a comprehensive, modular, and highly automated workflow to extract, to represent, and to analyze remotely sensed ice-wedge polygonal trough networks as a graph (i.e., network structure). With computer vision methods, we efficiently extract the trough locations as well as their geomorphometric information on trough depth and width from high-resolution digital elevation models and link these data within the graph. Further, we present and discuss the benefits of graph analysis algorithms for characterizing the erosional development of such thaw-affected landscapes. Based on our graph analysis, we show how thaw subsidence has progressed between 2009 and 2019 following burning at the Anaktuvuk River fire scar in northern Alaska, USA. We observed a considerable increase in the number of discernible troughs within the study area, while simultaneously the number of disconnected networks decreased from 54 small networks in 2009 to only six considerably larger disconnected networks in 2019. On average, the width of the troughs has increased by 13.86%, while the average depth has slightly decreased by 10.31%. Overall, our new automated approach allows for monitoring ice-wedge dynamics in unprecedented spatial detail, while simultaneously reducing the data to quantifiable geometric measures and spatial relationships. Article in Journal/Newspaper Arctic Ice permafrost wedge* Alaska University of Potsdam: publish.UP Arctic Remote Sensing 13 16 3098
spellingShingle ddc:620
Institut für Geowissenschaften
Rettelbach, Tabea
Langer, Moritz (Dr.)
Nitze, Ingmar
Jones, Benjamin
Helm, Veit
Freytag, Johann-Christoph
Grosse, Guido (Prof. Dr.)
A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title_full A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title_fullStr A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title_full_unstemmed A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title_short A quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
title_sort quantitative graph-based approach to monitoring ice-wedge trough dynamics in polygonal permafrost landscapes
topic ddc:620
Institut für Geowissenschaften
topic_facet ddc:620
Institut für Geowissenschaften
url https://publishup.uni-potsdam.de/frontdoor/index/index/docId/66045
https://doi.org/10.3390/rs13163098