A comparative analysis of deep learning models for accurate spatio-temporal soil moisture prediction
Soil moisture (SM) is essential for energy and water exchange between soil and atmosphere. Accurate prediction of its spatio-temporal occurrence is critical for climate, hydrology, and agriculture. This study fine-tunes and evaluates state-of-the-art deep learning models for spatio-temporal SM predi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2024.2441382 |
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