The Accuracy, Spatial Consistency, and Impact Factors of Global Cropland Products in Karst Landscapes: A Case Study of the Yunnan–Guizhou Plateau

Reliable cropland mapping in Karst landscapes is hindered by high topographic heterogeneity and landscape fragmentation. Focusing on the Yunnan–Guizhou Plateau in Southwest China, this study evaluates the accuracy and spatial consistency of seven global land cover products (i.e., GlobeLand30, CLCD, GLC_FCS30, CACD, ESA WorldCover, Esri Land Cover, and FROM-GLC10) against the Third National Land Survey released by China’s Ministry of Natural Resources. Furthermore, we employed Multiscale Geographically Weighted Regression (MGWR) to diagnose key impact factors. The results reveal that the 10 m ESA WorldCover offers superior reliability (OA = 0.81, R2 = 0.84), whereas GLC_FCS30 exhibits the weakest performance among the evaluated datasets (OA = 0.72, R2 = 0.29), highlighting significant uncertainty in this complex terrain. Crucially, MGWR diagnostics (adjusted R2=0.923) uncover how mapping uncertainty is driven by spatially non-stationary environmental constraints. Landscape fragmentation was identified as the primary global driver, exhibiting a consistent negative correlation with accuracy and indicating that the mixed pixel dilemma is the pervasive error source. In contrast, topographic slope operated as a dominant local constraint, with its inhibitory effect intensifying specifically in high-relief gorges where terrain shadowing compromises optical signals. Based on these mechanism diagnostics, we propose a region-adaptive decision framework integrating multi-source fusion and temporal logic to specifically target these topography- and fragmentation-induced uncertainties in future mapping.