Multidimensional Urban–Rural Integration Based on Factor Flows and Its Effects on Landscape Patterns: A Case Study of Nanjing, China

Abstract Urban–rural integration (URI) refers to coordinated development between cities and rural areas. While existing research addresses URI quantification, effects, and optimization, gaps remain in quantifying URI from the perspective of factor flows, analyzing its distribution across urban–fringe–rural regions, and examining URI’s impact on landscape patterns. This study analyzed Nanjing, which is a typical metropolitan city of China, using a machine learning method to identify urban, fringe, and rural areas, quantifying URI from economic, social, and spatial dimensions, and applied a Random Forest regression model combined with Shapley additive explanations analysis to examine URI’s influence on landscapes. Findings include the following: (1) Nanjing’s urban, fringe, and rural areas occupied 18.3%, 29.0%, and 52.7% in 2022, respectively. (2) Urban area had the highest URI estimations of all dimensions. Fringe area held the medium values, with lower social and spatial integration. URI in rural areas was the weakest. (3) URI showed significant effects in fringe and rural areas. In fringe zones, ecological land division was positively correlated with spatial integration, while construction land patterns were influenced by multidimensional URI dynamics. In rural zones, construction land connectivity was shaped by the synergy of spatial and social integration and service facility distribution. (4) Based on these findings, a differentiated zoning strategy was proposed to guide region-specific integration and landscape optimization. This study provides a new perspective on understanding URI, offering both theoretical and practical implications for landscape optimization.