Articles | Volume 17, issue 10
https://doi.org/10.5194/tc-17-4363-2023
https://doi.org/10.5194/tc-17-4363-2023
Research article
 | 
17 Oct 2023
Research article |  | 17 Oct 2023

Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions

Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila

Viewed

Total article views: 1,989 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,507 422 60 1,989 130 57 44
  • HTML: 1,507
  • PDF: 422
  • XML: 60
  • Total: 1,989
  • Supplement: 130
  • BibTeX: 57
  • EndNote: 44
Views and downloads (calculated since 02 Jan 2023)
Cumulative views and downloads (calculated since 02 Jan 2023)

Viewed (geographical distribution)

Total article views: 1,989 (including HTML, PDF, and XML) Thereof 1,943 with geography defined and 46 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Nov 2024
Short summary
Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.