Spatial Patterns and Multidimensional Drivers of Land Use Inefficiency in Quanzhou: Insights from Explainable Machine Learning

As urban development shifts from outward expansion to stock-based regeneration, inefficient urban land has become a critical constraint on land resource allocation, urban renewal, and sustainable spatial governance. To support differentiated urban renewal and sustainable land governance, this study examined the spatial patterns, factor contributions, and interaction mechanisms of inefficient land use in 2022 within the urban development boundary of Quanzhou, southeastern China. Based on the official 2022 citywide survey of inefficient urban land, multisource geographic and socioeconomic data were integrated with spatial statistical analysis, extreme gradient boosting (XGBoost), and shapley additive explanations (SHAP). The results show that 5396 inefficient land parcels were identified in 2022, covering 77.62 km². Industrial land accounted for the largest area share (59.23%), followed by residential land (38.67%) and commercial land (2.10%). Inefficient land showed a clear northwest-southeast orientation, extending across core urban areas, traditional industrial agglomeration zones, and county-level urban nodes. The Global Moran’s I reached 0.97, and High-High clusters were mainly located in Licheng District, southern Jinjiang City, and the county-level urban centers of Dehua and Yongchun, indicating concentration in old urban districts, traditional manufacturing agglomeration areas, and county-level built-up areas. The SHAP results show that industrial inefficiency was mainly associated with social and built-environment conditions, residential inefficiency with built-environment characteristics, and commercial inefficiency with ecological-location and social service conditions. The interaction analysis further indicates that industrial inefficiency was shaped by the overlap among transport accessibility, ecological-location attributes, surrounding urban value, and traditional production functions; residential inefficiency by the alignment among community service facilities, neighborhood space, population demand, and mobility conditions; and commercial inefficiency by the matching among development intensity, road and public transport capacity, population distribution, and service facility allocation. These findings suggest type-specific renewal strategies, including parcel consolidation and production-supporting function improvement for industrial land, neighborhood-scale service coordination for residential land, and functional matching among development intensity, road and public transport capacity, population distribution, and service facilities for commercial land.