Annual 10 m Mapping of Winter Fallow Fields in the Wanjiang Plain Using Sentinel-1/2 and a Random Forest–FR-Net Framework: Dynamics and Environmental Associations

Winter fallow fields (WFF) are widespread across humid subtropical croplands in the Yangtze River Economic Belt, exerting direct implications for annual land-use efficiency and winter production potential. However, acquiring fine-scale, year-to-year WFF information remains challenging due to frequent cloud contamination and the high fragmentation of agricultural parcels. Here, we mapped the annual 10 m WFF distribution in the Wanjiang Plain for six winter seasons (2019–2024). We employed a hierarchical mapping framework that integrates winter-stage Sentinel-1/2 composites with a Random Forest (RF) pre-classifier and a Fine Resolution Network (FR-Net) refinement module. Parcel-wise validation demonstrated robust and consistent performance across years (pooled OA = 0.969, F1-score = 0.969, MCC = 0.938). Spatiotemporal analyses revealed that WFF persistently occupied 52.3–65.6% of the regional cropland (7.59 × 103–9.52 × 103 km2), exhibiting a pronounced “hot-north, cold-south” spatial clustering. Approximately 52% of the cropland experienced high fallow recurrence (>67% frequency), forming stable high-recurrence cores. Furthermore, our MaxEnt association model (AUC = 0.739) identified relief amplitude, slope, and silt content as the most influential biophysical constraints. While these correlational variables act as proxies for underlying drainage and workability constraints rather than deterministic drivers, our high-fidelity 10-m WFF layers provide a consistent, policy-relevant baseline for hotspot-oriented screening and targeted winter-cropping optimization.