Coupling semi-empirical and machine learning model in high-resolution remote sensing soil moisture retrieval

Keyphrases

• Machine Learning Models 100%
• Fusion Model 100%
• High-resolution Remote Sensing 100%
• Soil Moisture Retrieval 100%
• Empirical Learning 100%
• Surface Soil Moisture 85%
• High-resolution 42%
• Physical Mechanism 42%
• Retrieval Study 42%
• High Spatial Resolution 28%
• Retrieval Practice 28%
• Retrieval Model 28%
• Synthetic Aperture Radar 28%
• Physical Machine 28%
• Machine Learning 14%
• Spatiotemporal 14%
• Effective Method 14%
• Generalization Ability 14%
• Modeling Capability 14%
• Soil Moisture Data 14%
• Predictive Models 14%
• Physical Model 14%
• Model Mechanism 14%
• Application Mode 14%
• Water Cycle 14%
• Retrieval-based 14%
• Machine Learning Modeling 14%
• Multi-source Datasets 14%
• Nonlinear Modeling 14%
• Radar-based 14%
• Multiple Fusion 14%
• Forest Cover Type 14%
• Earth Surface Systems 14%
• Land-air Interactions 14%
• Active Microwave Remote Sensing 14%
• Complementary Fusion 14%

Earth and Planetary Sciences

• Remote Sensing 100%
• Soil Moisture 100%
• Information Retrieval 100%
• Machine Learning 100%
• Regional Geography 16%
• Synthetic Aperture Radar 16%
• High Spatial Resolution 16%
• Earth Surface 8%
• Forest Cover 8%
• Microwave Remote Sensing 8%
• Air Land Interactions 8%

Chemical Engineering

• Learning System 100%
• Soil Moisture 100%
• Synthetic Aperture 28%