Abstract: This study examines how street patterns, metro stations, and urban function density influence pedestrian distribution in Tianjin, China. Thirteen neighborhoods from the city center and suburbs were selected for observation. Data on pedestrian and vehicle volumes were collected from 703 street segments. Regression models were employed to analyze the effects of street patterns, points of interest (POIs), and accessibility to vehicles and the metro on pedestrian volumes within each neighborhood and across the city. Results indicate that, collectively, local street connectivity and POIs significantly impact pedestrian distribution, while metro station proximity and vehicle accessibility have a lesser effect. On a neighborhood level, both local and city-scale street patterns influence pedestrian distribution. These findings suggest that street patterns serve as a foundation for metro stations to attract urban functions and pedestrian traffic.
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For more information, please visit: https://link.springer.com/article/10.1007/s40864-021-00152-9
