Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry

Thaw slumps are one of the most dynamic features in permafrost terrain. Improved temporal and spatial resolution monitoring of slump activity is required to better characterize their dynamics over the thaw season. We assess how a ground-based stationary camera array in a time-lapse configuration can...

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Bibliographic Details
Published in:Arctic Science
Main Authors: Lindsay Armstrong, Denis Lacelle, Robert H. Fraser, Steve Kokelj, Anders Knudby
Format: Article in Journal/Newspaper
Language:English
French
Published: Canadian Science Publishing 2018
Subjects:
geo
Online Access:https://doi.org/10.1139/as-2018-0016
https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:9413ebf3b1c548ad916ab7dd0f8b8638 2023-05-15T14:22:22+02:00 Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry Lindsay Armstrong Denis Lacelle Robert H. Fraser Steve Kokelj Anders Knudby 2018-12-01 https://doi.org/10.1139/as-2018-0016 https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638 en fr eng fre Canadian Science Publishing doi:10.1139/as-2018-0016 2368-7460 https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638 undefined Arctic Science, Vol 4, Iss 4, Pp 827-845 (2018) thermokarst permafrost remote sensing arctic geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2018 fttriple https://doi.org/10.1139/as-2018-0016 2023-01-22T19:11:13Z Thaw slumps are one of the most dynamic features in permafrost terrain. Improved temporal and spatial resolution monitoring of slump activity is required to better characterize their dynamics over the thaw season. We assess how a ground-based stationary camera array in a time-lapse configuration can be integrated with unmanned aerial vehicle (UAV)-based surveys and Structure-from-Motion processing to monitor the activity of thaw slumps at high temporal and spatial resolutions. We successfully constructed point-clouds and digital surface models of the headwall area of a thaw slump at 6- to 13-day intervals over the summer, significantly improving the decadal to annual temporal resolution of previous studies. The successfully modeled headwall portion of the slump revealed that headwall retreat rates were significantly correlated with mean daily air temperature, thawing degree-days, and average net short-wave radiation and suggest a two-phased slump activity. The main challenges were related to strong JPEG image compression, drifting camera clocks, and highly dynamic nature of the feature. Combined with annual UAV-based surveys, the proposed methodology can address temporal gaps in our understanding of factors driving thaw slump activity. Such insight could help predict how slumps could modify their behavior under changing climate. Article in Journal/Newspaper Arctic Arctic permafrost Thermokarst Unknown Arctic Arctic Science 4 4 827 845
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
French
topic thermokarst
permafrost
remote sensing
arctic
geo
envir
spellingShingle thermokarst
permafrost
remote sensing
arctic
geo
envir
Lindsay Armstrong
Denis Lacelle
Robert H. Fraser
Steve Kokelj
Anders Knudby
Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
topic_facet thermokarst
permafrost
remote sensing
arctic
geo
envir
description Thaw slumps are one of the most dynamic features in permafrost terrain. Improved temporal and spatial resolution monitoring of slump activity is required to better characterize their dynamics over the thaw season. We assess how a ground-based stationary camera array in a time-lapse configuration can be integrated with unmanned aerial vehicle (UAV)-based surveys and Structure-from-Motion processing to monitor the activity of thaw slumps at high temporal and spatial resolutions. We successfully constructed point-clouds and digital surface models of the headwall area of a thaw slump at 6- to 13-day intervals over the summer, significantly improving the decadal to annual temporal resolution of previous studies. The successfully modeled headwall portion of the slump revealed that headwall retreat rates were significantly correlated with mean daily air temperature, thawing degree-days, and average net short-wave radiation and suggest a two-phased slump activity. The main challenges were related to strong JPEG image compression, drifting camera clocks, and highly dynamic nature of the feature. Combined with annual UAV-based surveys, the proposed methodology can address temporal gaps in our understanding of factors driving thaw slump activity. Such insight could help predict how slumps could modify their behavior under changing climate.
format Article in Journal/Newspaper
author Lindsay Armstrong
Denis Lacelle
Robert H. Fraser
Steve Kokelj
Anders Knudby
author_facet Lindsay Armstrong
Denis Lacelle
Robert H. Fraser
Steve Kokelj
Anders Knudby
author_sort Lindsay Armstrong
title Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
title_short Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
title_full Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
title_fullStr Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
title_full_unstemmed Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry
title_sort thaw slump activity measured using stationary cameras in time-lapse and structure-from-motion photogrammetry
publisher Canadian Science Publishing
publishDate 2018
url https://doi.org/10.1139/as-2018-0016
https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
permafrost
Thermokarst
genre_facet Arctic
Arctic
permafrost
Thermokarst
op_source Arctic Science, Vol 4, Iss 4, Pp 827-845 (2018)
op_relation doi:10.1139/as-2018-0016
2368-7460
https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638
op_rights undefined
op_doi https://doi.org/10.1139/as-2018-0016
container_title Arctic Science
container_volume 4
container_issue 4
container_start_page 827
op_container_end_page 845
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