Brief communication: Monitoring snow depth using small, cheap, and easy-to-deploy snow–ground interface temperature sensors

<p>Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We trained a random forest machine learning model to predict snow depth from variability in snow–ground interface temperature. The model performed well on A...

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Bibliographic Details
Main Authors: C. L. Bachand, C. Wang, B. Dafflon, L. N. Thomas, I. Shirley, S. Maebius, C. M. Iversen, K. E. Bennett
Format: Article
Language:English
Published: Copernicus Publications 2025-01-01
Series:The Cryosphere
Online Access:https://tc.copernicus.org/articles/19/393/2025/tc-19-393-2025.pdf
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