Articles | Volume 17, issue 10
https://doi.org/10.5194/tc-17-4363-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-4363-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
Leo-Juhani Meriö
CORRESPONDING AUTHOR
Water, Energy and Environmental Engineering, Faculty of Technology, University of Oulu, Oulu, 90014, Finland
Water Resources, Finnish Environment Institute (Syke), 90014, Oulu, Finland
Anssi Rauhala
Civil Engineering, Faculty of Technology, University of Oulu, Oulu, 90014, Finland
Pertti Ala-aho
Water, Energy and Environmental Engineering, Faculty of Technology, University of Oulu, Oulu, 90014, Finland
Anton Kuzmin
Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, 80101, Finland
Pasi Korpelainen
Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, 80101, Finland
Timo Kumpula
Department of Geographical and Historical Studies, University of Eastern Finland, Joensuu, 80101, Finland
Bjørn Kløve
Water, Energy and Environmental Engineering, Faculty of Technology, University of Oulu, Oulu, 90014, Finland
Hannu Marttila
Water, Energy and Environmental Engineering, Faculty of Technology, University of Oulu, Oulu, 90014, Finland
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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.
Information on seasonal snow cover is essential in understanding snow processes and operational...