Work

Effects of station-area built environment on urban rail transit passenger flow

Year: 2026

Type: article

Abstract: Global urban rail transit (URT) faces operational inefficiencies due to spatiotemporal mismatches between stations and urban functions. Existing research overemphasizes average daily ridership, lacking insights into built environment effects’ variations by station type, time and spatial scale. This study develops an integrated framework of station classification and multiscale geographically weighted regression (MGWR) to explore built environment-passenger flow mechanisms, with Changsha as a case. K-Means clustering categorizes stations into residential, employment and mixed-use types, and MGWR is compared with OLS and GWR models. Key findings: built environment impacts show distinct spatiotemporal heterogeneity, functional-type dependence and scale variability; educational/cultural facilities and entrance/exit numbers steadily drive passenger flow; office density has divergent effects across station types and peak/off-peak periods. The framework identifies variables’ operational scales, offering a refined analytical tool for spatial patterns, deepening station-city dynamic theories and enabling tailored URT planning governance.

Source: Transportation Research Part D Transport and Environment

DOI: 10.1016/j.trd.2026.105630

Authors: Xiaolan Wang, Wenbin Tang, Hongyan Yan, Qifeng Xu, Mingxia Shu

Institutions: Hunan University of Finance and Economics, Changsha University of Science and Technology

Language: English

Topic: Urban Transport and Accessibility

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,450