Articles | Volume 14, issue 6
The Cryosphere, 14, 1919–1935, 2020
The Cryosphere, 14, 1919–1935, 2020
Research article
15 Jun 2020
Research article | 15 Jun 2020

Improving sub-canopy snow depth mapping with unmanned aerial vehicles: lidar versus structure-from-motion techniques

Phillip Harder et al.

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Cited articles

Aksamit, N. and Pomeroy, J. W.: Scale Interactions in Turbulence for Mountain Blowing snow, J. Hydrometeorol., 19, 305–320,, 2018. 
Bhardwaj, A., Sam, L., Bhardwaj, A., and Martín-Torres, F. J.: LiDAR remote sensing of the cryosphere: Present applications and future prospects, Remote Sens. Environ., 177, 125–143,, 2016. 
Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry, The Cryosphere, 9, 229–243,, 2015. 
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075–1088,, 2016. 
Busseau, B.-C., Royer, A., Roy, A., Langlois, A., and Domine, F.: Analysis of snow-vegetation interacitions in the low arctic-subarctic transition zone (northeastern Canada), Phys. Geogr., 38, 159–175,, 2017. 
Short summary
Unmanned-aerial-vehicle-based (UAV) structure-from-motion (SfM) techniques have the ability to map snow depths in open areas. Here UAV lidar and SfM are compared to map sub-canopy snowpacks. Snow depth accuracy was assessed with data from sites in western Canada collected in 2019. It is demonstrated that UAV lidar can measure the sub-canopy snow depth at a high accuracy, while UAV-SfM cannot. UAV lidar promises to quantify snow–vegetation interactions at unprecedented accuracy and resolution.