Identification of Barriers and Drivers of Multifactor Flows in Smart Urban–Rural Networks: An Integrated Geospatial Analytics Framework

Against a global backdrop of industrialization and urbanization, precise measurement of multifactor flows and systematic identification of barriers and drivers are critical for optimizing resource allocation in smart regional development. This study develops an integrated geospatial analytic framework that incorporates mobile signaling data and POI data to quantify the intensity, barriers, and driving mechanisms of urban–rural factor flows in Huzhou City at the township scale. Key findings reveal the following. (1) Urban–rural factor flows exhibit significant spatial polarization, with less than 20% of connections accounting for the majority of flow intensity. The structure shows clear core–periphery differentiation, further shaped by inner heterogeneity and metropolitan spillovers. (2) Barriers demonstrate complex and uneven spatial distributions, with 45.37% of the integrated flow intervals experiencing impediments. Critically, some nodes act as both facilitators and obstacles, depending on the flow type and direction, revealing a metamodern tension between promotion and impairment. (3) Economic vitality plays a crucial role in driving urban–rural factor flow, with different factors having complex, often synergistic or nonlinear effects on both single and integrated flows. The study advances the theoretical understanding of heterogeneous spatial structures in urban–rural systems and provides a replicable analytical framework for diagnosing factor flows in small and medium-sized cities. These insights form a critical basis for designing targeted and adaptive regional governance strategies.