Articles | Volume 10, issue 2
The Cryosphere, 10, 511–522, 2016
https://doi.org/10.5194/tc-10-511-2016
The Cryosphere, 10, 511–522, 2016
https://doi.org/10.5194/tc-10-511-2016
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.

Related authors

Hydrological response of a peri-urban catchment exploiting conventional and unconventional rainfall observations: the case study of Lambro Catchment
Greta Cazzaniga, Carlo De Michele, Michele D'Amico, Cristina Deidda, Antonio Ghezzi, and Roberto Nebuloni
Hydrol. Earth Syst. Sci., 26, 2093–2111, https://doi.org/10.5194/hess-26-2093-2022,https://doi.org/10.5194/hess-26-2093-2022, 2022
Short summary
A local model of snow–firn dynamics and application to the Colle Gnifetti site
Fabiola Banfi and Carlo De Michele
The Cryosphere, 16, 1031–1056, https://doi.org/10.5194/tc-16-1031-2022,https://doi.org/10.5194/tc-16-1031-2022, 2022
Short summary
Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021,https://doi.org/10.5194/nhess-21-1867-2021, 2021
Short summary
Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies
Marco Bongio, Ali Nadir Arslan, Cemal Melih Tanis, and Carlo De Michele
The Cryosphere, 15, 369–387, https://doi.org/10.5194/tc-15-369-2021,https://doi.org/10.5194/tc-15-369-2021, 2021
Short summary
A local model of snow-firn dynamics and application to Colle Gnifetti site
Fabiola Banfi and Carlo De Michele
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-357,https://doi.org/10.5194/tc-2020-357, 2021
Manuscript not accepted for further review
Short summary

Related subject area

Seasonal Snow
Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022,https://doi.org/10.5194/tc-16-2147-2022, 2022
Short summary
Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022,https://doi.org/10.5194/tc-16-1281-2022, 2022
Short summary
Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022,https://doi.org/10.5194/tc-16-1007-2022, 2022
Short summary
Past changes in natural and managed snow reliability of French Alps ski resorts from 1961 to 2019
Lucas Berard-Chenu, Hugues François, Emmanuelle George, and Samuel Morin
The Cryosphere, 16, 863–881, https://doi.org/10.5194/tc-16-863-2022,https://doi.org/10.5194/tc-16-863-2022, 2022
Short summary
Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest of eastern Canada
Achut Parajuli, Daniel F. Nadeau, François Anctil, and Marco Alves
The Cryosphere, 15, 5371–5386, https://doi.org/10.5194/tc-15-5371-2021,https://doi.org/10.5194/tc-15-5371-2021, 2021
Short summary

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, https://doi.org/10.1002/hyp.1319, 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, https://doi.org/10.1002/hyp.7195, 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, https://doi.org/10.1016/j.advwatres.2012.12.009, 2013.
Download
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.