Abstract
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.
Highlights
The negative trend in glacier mass balance is pronounced in the Canadian Arctic, where rapid glacier recession has been documented in the early 21st century [1,2,3,4,5]
Understanding future glacier mass changes in this difficult to access region depends on accurate monitoring and modelling of glacier mass balance. Research in this field has relied on sparse data points and significant generalizations [6], but new technologies, such as unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry (SfM), are becoming widely used tools for improving understanding of glacier change [7,8]
Unmanned aerial vehicle surveys were conducted to reconstruct a glacier surface, with accuracies higher than previously reported in the literature allowing for small changes to be measured
Summary
The negative trend in glacier mass balance is pronounced in the Canadian Arctic, where rapid glacier recession has been documented in the early 21st century [1,2,3,4,5]. Research in this field has relied on sparse data points and significant generalizations [6], but new technologies, such as unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry (SfM), are becoming widely used tools for improving understanding of glacier change [7,8]. Advances in UAV technology has enabled their widespread use in scientific research [9]. They are a attractive tool for glaciological research due to their ability to collect data over wider areas and inaccessible regions of glaciers, with relatively low costs and efforts. Glaciological studies using UAVs have tracked glacier motion (e.g., [7,10,14]); measured seasonal or multi-year melt (e.g., [7,10,13]); analyzed calving and crevasse dynamics (e.g., [12,15,16]); and mapped surface characteristics such as drainage networks [11], albedo [17], debris cover [18], and cryoconite holes [19]
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