Exploring the spatially and temporally varying impacts of built environment factors on rail transit ridership

Abstract

This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations, aiming to enhance rail transit operational efficiency and inform station planning and development. Data from 159 metro stations in Nanjing, collected over a 14-d period, were analyzed to identify changes in weekday and weekend ridership patterns. The analysis included explanatory variables grouped into three categories: urban spatial variables, socioeconomic variables, and transit service variables. A geographically and temporally weighted regression (GTWR) model was developed, and its performance was compared with that of ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment. In addition, the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions, revealing distinct patterns. Notably, the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays. These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.

Keywords

built environment / rail transit ridership / spatiotemporal analysis / geographically and temporally weighted regression(GTWR)

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Funding

National Key Research and Development Program of China(2022YFC3800201)