Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska
Terrestrial laser scanners (TLS) allow large and complex landforms to be rapidly surveyed at previously unattainable point densities. Many change detection methods have been employed to make use of these rich data sets, including cloud to mesh (C2M) comparisons and Multiscale Model to Model Cloud Co...
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ftmdpi:oai:mdpi.com:/2072-4292/5/6/2813/ 2023-08-20T04:04:58+02:00 Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska Theodore Barnhart Benjamin Crosby agris 2013-05-31 application/pdf https://doi.org/10.3390/rs5062813 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs5062813 https://creativecommons.org/licenses/by/3.0/ Remote Sensing; Volume 5; Issue 6; Pages: 2813-2837 terrestrial laser scanning topographic change detection error analysis thermokarst Arctic permafrost Text 2013 ftmdpi https://doi.org/10.3390/rs5062813 2023-07-31T20:32:46Z Terrestrial laser scanners (TLS) allow large and complex landforms to be rapidly surveyed at previously unattainable point densities. Many change detection methods have been employed to make use of these rich data sets, including cloud to mesh (C2M) comparisons and Multiscale Model to Model Cloud Comparison (M3C2). Rather than use simulated point cloud data, we utilized a 58 scan TLS survey data set of the Selawik retrogressive thaw slump (RTS) to compare C2M and M3C2. The Selawik RTS is a rapidly evolving permafrost degradation feature in northwest Alaska that presents challenging survey conditions and a unique opportunity to compare change detection methods in a difficult surveying environment. Additionally, this study considers several error analysis techniques, investigates the spatial variability of topographic change across the feature and explores visualization techniques that enable the analysis of this spatiotemporal data set. C2M reports a higher magnitude of topographic change over short periods of time (~12 h) and reports a lower magnitude of topographic change over long periods of time (~four weeks) when compared to M3C2. We found that M3C2 provides a better accounting of the sources of uncertainty in TLS change detection than C2M, because it considers the uncertainty due to surface roughness and scan registration. We also found that localized areas of the RTS do not always approximate the overall retreat of the feature and show considerable spatial variability during inclement weather; however, when averaged together, the spatial subsets approximate the retreat of the entire feature. New data visualization techniques are explored to leverage temporally and spatially continuous data sets. Spatially binning the data into vertical strips along the headwall reduced the spatial complexity of the data and revealed spatiotemporal patterns of change. Text Arctic permafrost Thermokarst Alaska MDPI Open Access Publishing Arctic Remote Sensing 5 6 2813 2837 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
terrestrial laser scanning topographic change detection error analysis thermokarst Arctic permafrost |
spellingShingle |
terrestrial laser scanning topographic change detection error analysis thermokarst Arctic permafrost Theodore Barnhart Benjamin Crosby Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
topic_facet |
terrestrial laser scanning topographic change detection error analysis thermokarst Arctic permafrost |
description |
Terrestrial laser scanners (TLS) allow large and complex landforms to be rapidly surveyed at previously unattainable point densities. Many change detection methods have been employed to make use of these rich data sets, including cloud to mesh (C2M) comparisons and Multiscale Model to Model Cloud Comparison (M3C2). Rather than use simulated point cloud data, we utilized a 58 scan TLS survey data set of the Selawik retrogressive thaw slump (RTS) to compare C2M and M3C2. The Selawik RTS is a rapidly evolving permafrost degradation feature in northwest Alaska that presents challenging survey conditions and a unique opportunity to compare change detection methods in a difficult surveying environment. Additionally, this study considers several error analysis techniques, investigates the spatial variability of topographic change across the feature and explores visualization techniques that enable the analysis of this spatiotemporal data set. C2M reports a higher magnitude of topographic change over short periods of time (~12 h) and reports a lower magnitude of topographic change over long periods of time (~four weeks) when compared to M3C2. We found that M3C2 provides a better accounting of the sources of uncertainty in TLS change detection than C2M, because it considers the uncertainty due to surface roughness and scan registration. We also found that localized areas of the RTS do not always approximate the overall retreat of the feature and show considerable spatial variability during inclement weather; however, when averaged together, the spatial subsets approximate the retreat of the entire feature. New data visualization techniques are explored to leverage temporally and spatially continuous data sets. Spatially binning the data into vertical strips along the headwall reduced the spatial complexity of the data and revealed spatiotemporal patterns of change. |
format |
Text |
author |
Theodore Barnhart Benjamin Crosby |
author_facet |
Theodore Barnhart Benjamin Crosby |
author_sort |
Theodore Barnhart |
title |
Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
title_short |
Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
title_full |
Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
title_fullStr |
Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
title_full_unstemmed |
Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska |
title_sort |
comparing two methods of surface change detection on an evolving thermokarst using high-temporal-frequency terrestrial laser scanning, selawik river, alaska |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2013 |
url |
https://doi.org/10.3390/rs5062813 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic permafrost Thermokarst Alaska |
genre_facet |
Arctic permafrost Thermokarst Alaska |
op_source |
Remote Sensing; Volume 5; Issue 6; Pages: 2813-2837 |
op_relation |
https://dx.doi.org/10.3390/rs5062813 |
op_rights |
https://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.3390/rs5062813 |
container_title |
Remote Sensing |
container_volume |
5 |
container_issue |
6 |
container_start_page |
2813 |
op_container_end_page |
2837 |
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1774715382321381376 |