Enhancing the Spatial Applicability of SMAP Soil Moisture Using Multi-Stage Machine Learning Downscaling
Results indicate that multi-stage machine learning downscaling can enhance spatial interpretability and strengthen the applicability of SMAP SM for agricultural monitoring, while preserving broad consistency with the original passive microwave retrieval and providing a practical baseline for regional refinement.