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...
Published in: | Arctic Science |
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Canadian Science Publishing
2018
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Online Access: | https://doi.org/10.1139/as-2018-0016 https://doaj.org/article/9413ebf3b1c548ad916ab7dd0f8b8638 |
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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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1766294978040954880 |