Coupling Space Syntax and Behavioral Mapping to Evaluate and Optimize Pedestrian Networks in Shanghai Metro Station Areas

Abstract

Pedestrian systems in metro station areas fulfill both transit connectivity and public-activity functions, yet mismatches between spatial potential and behavioral performance are frequently observed in practice. To enhance the overall performance of such pedestrian systems, it is essential to examine the coupling mechanisms from both structural and behavioral dimensions. This study selects two representative metro station areas in Shanghai—one general type and one cluster type. A dual-dimension indicator system covering physical and perceptual attributes are established. Spatial configurations is analyzed using space syntax, while behavioral and perceptual performance is quantified through on-site observations. A coupling-coordination model is further adopted to evaluate the structure–behavior matching relationship, supplemented by micro-scale spatial analysis to reveal contextual causes. The two station-area types exhibit distinct coupling characteristics: general-type stations show a “high-potential–low-activity” pattern (e.g., U₁=0.368, U₂=0.387, D=0.614), where structural accessibility fails to translate into a stay and social demands; cluster-type stations present a “high-potential–high-activity–high-constraint” pattern (e.g., U₁=0.422, U₂=0.510, D=0.681), where intensive activities are limited by visual obstruction and environmental pressure. This study identifies differentiated coupling features and corresponding optimization paths, demonstrating that determining spatial interventions based on dual-dimension coupling relations is essential for enhancing both spatial quality and behavioral experience in station-area pedestrian system planning and regeneration.