Spatiotemporal Analysis of Rice Cropping Patterns and Land Degradation Driven by Land Use and Land Cover Change in Jiangsu, China

This study examines recent single‐season rice (SSR) dynamics, land use/land cover (LULC) transition, and land degradation in Jiangsu Province, China, using an integrated remote‐sensing workflow on Google Earth Engine within a recent 2021–2024 monitoring framework. Annual SSR maps for 2021–2024 were produced from Sentinel‐1 and Sentinel‐2 imagery using phenology‐based pseudo‐label generation and annual random forest classification. Annual LULC transitions were derived from the ESRI 10 m land‐cover product, and degradation patterns were assessed from Landsat‐based EVI2 trends. Classification results showed stable, high accuracy across all years, supporting reliable interannual comparisons. SSR remained concentrated in the north‐central agricultural belt, but the total mapped area declined by 2.17% over the study period, indicating a gradual contraction rather than an abrupt collapse. Cropland remained the dominant land class, yet net cropland change was negative, with crops‐to‐built conversion representing the largest loss pathway. Degradation analysis showed that improvement dominated at the provincial scale, whereas decline was spatially selective and concentrated in localized hotspots linked to crop stress and transition zones. The study demonstrates that agricultural pressure in Jiangsu is uneven and transition‐driven, providing spatial evidence for targeted cropland protection, climate‐resilient land management, and remote‐sensing‐based agricultural monitoring for sustainable regional planning decisions. The study advances recent agricultural monitoring in Jiangsu by linking rice‐system change, land‐cover transition, and degradation hotspots within one transition‐focused spatial framework.