Multi-scale OPGD uncovers spatial pattern and influencing factors of rural settlements in the Minjiang River Basin

Abstract

Rapid urbanization and industrialization are reshaping rural systems, necessitating a thorough analysis of their spatial patterns and driving forces. This study conducted cross-sectional analysis of rural settlement in the Minjiang River Basin (MRB) for the year 2020, using rural-settlement land data derived from annual China Land Cover Dataset (CLCD). Settlement scale was defined as the total area of rural settlement land within each analysis grid cell. was characterized using spatial analysis methods. Spatial analysis methods including Average Nearest Neighbor (ANN), Kernel Density Estimation (KDE), and Hot Spot Analysis applied to characterize the spatial pattern of rural settlements. An optimal analysis grid was identified through scale sensitivity testing, and the Optimal Parameter Geodetector (OPGD) was subsequently applied to examine the associated mechanisms of spatial differentiation in settlement scale. The results indicate that: (1) Rural settlements in the MRB exhibit a significant clustered distribution at the global scale (R = 0.698, Z = − 30.08), manifesting a "one primary core and multiple sub-cores" structure and a distinct Northwest-Southeast axial, with the spatial centroid notably shifted toward coastal lowlands. (2) A 4 km grid size produced the highest mean q-value among the six tested scales. (3) Factor detection reveals that the Normalized Difference Vegetation Index (NDVI, q = 0.116) and road network density ( q = 0.091) showed the strongest spatial stratification in driving settlement scale differentiation. (4) All factor interactions exhibit enhancement effects; notably, the nonlinear enhancement between road network density and topographic relief is the most significant ( q = 0.147). These findings provide decision support for differentiated rural planning in the MRB and offer a valuable reference for spatial analysis and influential factor research in regions with complex terrain.