4.7 Article

High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 150, Issue -, Pages 93-103

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.04.025

Keywords

UAV; Photogrammetry; DEM differencing; Himalaya; Glacier dynamics; Climate change; Ice cliffs; Supra-glacial ponds

Funding

  1. ICIMOD Innovation Fund
  2. Utrecht University
  3. Netherlands Organization for Scientific Research
  4. Norwegian government

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Himalayan glacier tongues are commonly debris covered and they are an important source of melt water. However, they remain relatively unstudied because of the inaccessibility of the terrain and the difficulties in field work caused by the thick debris mantles. Observations of debris-covered glaciers are therefore scarce and airborne remote sensing may bridge the gap between scarce field observations and coarse resolution space-borne remote sensing. In this study we deploy an Unmanned Aerial Vehicle (UAV) before and after the melt and monsoon season (May and October 2013) over the debris-covered tongue of the Lirung Glacier in Nepal. Based on stereo-imaging and the structure for motion algorithm we derive highly detailed ortho-mosaics and digital elevation models (DEMs), which we geometrically correct using differential GPS observations collected in the field. Based on DEM differencing and manual feature tracking we derive the mass loss and the surface velocity of the glacier at a high spatial accuracy. On average, mass loss is limited and the surface velocity is very small. However, the spatial variability of melt rates is very high, and' ice cliffs and supra-glacial ponds show mass losses that can be an order of magnitude higher than the average. We suggest that future research should focus on the interaction between supra-glacial ponds, ice cliffs and englacial hydrology to further understand the dynamics of debris-covered glaciers. Finally, we conclude that UAV deployment has large potential in glaciology and it may revolutionize methods currently applied in studying glacier surface features. (C) 2014 Elsevier Inc All rights reserved.

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