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July 27, 2026International Journal of Applied Earth Observation and GeoinformationOpen Access

PLGF-NET: A Physics-Guided Local-Global fusion network for GNSS-R high wind speed retrieval

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Authors

XXXinzhe XuMSMinfeng SongXHXiufeng He

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Overview

Randomized trial demonstrates a novel physics-guided approach improving wind speed retrieval in high-wind marine environments, suggesting enhanced accuracy in satellite monitoring.

Key Points

  • This study aims to improve the accuracy of global sea surface wind speed retrieval under high-wind conditions using a new physics-guided approach.
  • Introduced the Physics-Guided Local-Global Fusion Network (PLGF-NET) framework.
  • Developed the Comprehensive Difficulty Score (CDS) for hierarchical sampling of Delay-Doppler Maps (DDMs).
  • Implemented a Physics-Guided Spatial Attention (PGSA) mechanism aiding feature purification.
  • Achieved an overall root mean square error (RMSE) of 1.38 m/s.
  • Reduced high-wind RMSE to 2.40 m/s, correcting systematic negative biases.
  • Demonstrated robustness through a physics-data dual-driven paradigm.

Cite This Study

Xu et al. (2026) studied this question.

synapsesocial.com/papers/6a67007840bca442e0d4a29ahttps://doi.org/10.1016/j.jag.2026.105493
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