Articles | Volume 10, issue 2
The Cryosphere, 10, 511–522, 2016
The Cryosphere, 10, 511–522, 2016
Research article
04 Mar 2016
Research article | 04 Mar 2016

Using a fixed-wing UAS to map snow depth distribution: an evaluation at peak accumulation

Carlo De Michele et al.

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Manuscript not accepted for further review
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Cited articles

Agisoft: Agisoft PhotoScan User Manual Professional Edition, Version 1.1, 2014.
Anderton, S. P., White, S. M., and Alvera, B.: Evaluation of spatial variability in snow water equivalent for a high mountain catchment, Hydrol. Process., 18, 435–453,, 2004.
Avanzi, F., De Michele, C., Ghezzi, A., Jommi, C., and Pepe, M.: A processing modeling routine to use SNOTEL hourly data in snowpack dynamic models, Adv. Water Resour., 73, 16–29, 2014.
Bavay, M., Lehning, M., Jonas, T., and Löwe, H.: Simulations of future snow cover and discharge in Alpine headwater catchments, Hydrol. Process., 23, 95–108,, 2009.
Bavay, M., Grünewald, T., and Lehning, M.: Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland, Adv. Water Resour., 55, 4–16,, 2013.
Short summary
We investigate snow depth distribution at peak accumulation over a small Alpine area using photogrammetry-based surveys with a fixed wing unmanned aerial system. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to -0.073 m. Moreover, in this case study snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m.