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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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-01-01
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| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/19/393/2025/tc-19-393-2025.pdf |
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