The Cryosphere
The Cryosphere
TC
Articles | Volume 17, issue 12
Articles | Volume 17, issue 12
https://doi.org/10.5194/tc-17-5317-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-5317-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 12
Research article
 | 
15 Dec 2023
Research article |  | 15 Dec 2023

A random forest approach to quality-checking automatic snow-depth sensor measurements

Giulia Blandini, Francesco Avanzi, Simone Gabellani, Denise Ponziani, Hervé Stevenin, Sara Ratto, Luca Ferraris, and Alberto Viglione

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Latest update: 23 Nov 2024
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Short summary
Automatic snow depth data are a valuable source of information for hydrologists, but they also tend to be noisy. To maximize the value of these measurements for real-world applications, we developed an automatic procedure to differentiate snow cover from grass or bare ground data, as well as to detect random errors. This procedure can enhance snow data quality, thus providing more reliable data for snow models.
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