Urban dynamics unveiled: A comprehensive analysis of Beijing’s subway evolution over the past decade

Amidst the ongoing transformation of urban landscapes worldwide, this study examines the dynamic evolution of Beijing’s urban rail transit network from 2013 to 2022, focusing on the interplay between urban spatial changes and passenger travel behavior. Utilizing an enhanced node-place model and a sophisticated stacking ensemble machine learning approach, we analyze a decade of subway station development and the shifting transit patterns within the city’s spatial structure. Our findings reveal a distinct phase of renovation and refinement in Beijing’s subway network, emphasizing the evolving role of node characteristics and place indicators in influencing ridership. By integrating diverse data sources, this study deepens our understanding of the complex relationships between urban rail transit, spatial dynamics, and ridership patterns. The insights gained offer valuable guidance for both subway renovation projects and emerging cities, addressing existing knowledge gaps and providing practical recommendations for policymakers and urban planners working to optimize transit systems in rapidly evolving metropolitan environments.