Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys

Current understanding of glacier mass balance changes under changing climate is limited by scarcity of in situ measurements in both time and space, as well as resolution of remote sensing products. Recent innovations in unmanned aerial vehicles (UAVs), as well as structure-from-motion photogrammetry...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: Eleanor A. Bash, Brian J. Moorman, Allison Gunther
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2018
Subjects:
UAV
Online Access:https://doi.org/10.3390/rs10101547
id ftmdpi:oai:mdpi.com:/2072-4292/10/10/1547/
record_format openpolar
spelling ftmdpi:oai:mdpi.com:/2072-4292/10/10/1547/ 2023-08-20T04:04:24+02:00 Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys Eleanor A. Bash Brian J. Moorman Allison Gunther agris 2018-09-26 application/pdf https://doi.org/10.3390/rs10101547 EN eng Multidisciplinary Digital Publishing Institute Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs10101547 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 10; Pages: 1547 UAV structure-from-motion photogrammetry change detection glacier melt Canadian Arctic Text 2018 ftmdpi https://doi.org/10.3390/rs10101547 2023-07-31T21:44:55Z Current understanding of glacier mass balance changes under changing climate is limited by scarcity of in situ measurements in both time and space, as well as resolution of remote sensing products. Recent innovations in unmanned aerial vehicles (UAVs), as well as structure-from-motion photogrammetry (SfM), have led to increased use of digital imagery to derive topographic data in great detail in many fields, including glaciology. This study tested the capability of UAV surveys to detect surface changes over glacier ice during a three-day period in July 2016. Three UAV imaging missions were conducted during this time over 0.185 km 2 of the ablation area of Fountain Glacier, NU. These were processed with the SfM algorithms in Agisoft Photoscan Professional and overall accuracies of the resulting point clouds ranged from 0.030 to 0.043 m. The high accuracy of point clouds achieved here is primarily a result of a small ground sampling distance (0.018 m), and is also influenced by GPS precision. Glacier surface change was measured through differencing of point clouds and change was compared to ablation stake measurements. Surface change measured with the UAV-SfM method agreed with the coincident ablation stake measurements in most instances, with RMSE values of 0.033, 0.028, and 0.042 m for one-, two-, and three-day periods, respectively. Total specific melt over the study area measured with the UAV was 0.170 m water equivalent (w.e.), while interpolation of ablation measurements resulted in 0.144 m w.e. Using UAVs to measure small changes in glacier surfaces will allow for new investigations of distribution of mass balance measurements. Text Arctic MDPI Open Access Publishing Arctic Fountain Glacier ENVELOPE(161.633,161.633,-77.683,-77.683) Remote Sensing 10 10 1547
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic UAV
structure-from-motion photogrammetry
change detection
glacier melt
Canadian Arctic
spellingShingle UAV
structure-from-motion photogrammetry
change detection
glacier melt
Canadian Arctic
Eleanor A. Bash
Brian J. Moorman
Allison Gunther
Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
topic_facet UAV
structure-from-motion photogrammetry
change detection
glacier melt
Canadian Arctic
description Current understanding of glacier mass balance changes under changing climate is limited by scarcity of in situ measurements in both time and space, as well as resolution of remote sensing products. Recent innovations in unmanned aerial vehicles (UAVs), as well as structure-from-motion photogrammetry (SfM), have led to increased use of digital imagery to derive topographic data in great detail in many fields, including glaciology. This study tested the capability of UAV surveys to detect surface changes over glacier ice during a three-day period in July 2016. Three UAV imaging missions were conducted during this time over 0.185 km 2 of the ablation area of Fountain Glacier, NU. These were processed with the SfM algorithms in Agisoft Photoscan Professional and overall accuracies of the resulting point clouds ranged from 0.030 to 0.043 m. The high accuracy of point clouds achieved here is primarily a result of a small ground sampling distance (0.018 m), and is also influenced by GPS precision. Glacier surface change was measured through differencing of point clouds and change was compared to ablation stake measurements. Surface change measured with the UAV-SfM method agreed with the coincident ablation stake measurements in most instances, with RMSE values of 0.033, 0.028, and 0.042 m for one-, two-, and three-day periods, respectively. Total specific melt over the study area measured with the UAV was 0.170 m water equivalent (w.e.), while interpolation of ablation measurements resulted in 0.144 m w.e. Using UAVs to measure small changes in glacier surfaces will allow for new investigations of distribution of mass balance measurements.
format Text
author Eleanor A. Bash
Brian J. Moorman
Allison Gunther
author_facet Eleanor A. Bash
Brian J. Moorman
Allison Gunther
author_sort Eleanor A. Bash
title Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
title_short Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
title_full Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
title_fullStr Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
title_full_unstemmed Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys
title_sort detecting short-term surface melt on an arctic glacier using uav surveys
publisher Multidisciplinary Digital Publishing Institute
publishDate 2018
url https://doi.org/10.3390/rs10101547
op_coverage agris
long_lat ENVELOPE(161.633,161.633,-77.683,-77.683)
geographic Arctic
Fountain Glacier
geographic_facet Arctic
Fountain Glacier
genre Arctic
genre_facet Arctic
op_source Remote Sensing; Volume 10; Issue 10; Pages: 1547
op_relation Remote Sensing in Geology, Geomorphology and Hydrology
https://dx.doi.org/10.3390/rs10101547
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs10101547
container_title Remote Sensing
container_volume 10
container_issue 10
container_start_page 1547
_version_ 1774714782682710016