Accurate sub-seasonal root-zone soil moisture prediction using attention-based autoregressive transfer learning and SMAP data

Accurate sub-seasonal root-zone soil moisture prediction using attention-based autoregressive transfer learning and SMAP data

Root zone soil moisture (RZSM) is an important hydrological variable for agricultural planning and water resources management. The Soil Moisture Active Passive Level 4 (SMAP L4) data demonstrates great value in RZSM estimation. Accurate sub-seasonal RZSM prediction based on SMAP L4 holds great signi...

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Bibliographic Details
Main Authors: Lei Xu, Xihao Zhang, Xi Zhang, Tingtao Wu, Hongchu Yu, Wenying Du, Zeqiang Chen, Nengcheng Chen
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
RZSM
SMAP
Multi-head self-attention
Autoregressive
Transfer learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843225001797
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