Citation

Wei M. J. Transp. Geogr. 2022; 98: e103242.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.jtrangeo.2021.103242

PMID

unavailable

Abstract

Drawing on transit smart card data and weather station records over a 12-month period, this study investigates the influence of local weather conditions on public transit ridership in Brisbane, Australia. Based on the statistical distribution of transit ridership, this study applies a suite of geographically weighted negative binomial regression models to capture the weather-transit ridership relationship at both daily and half-hourly levels. The results reveal that weather exerts significant effects on transit ridership; its effects vary by passenger type and are not fixed across locations and temporal periods. In general, senior passengers are the most sensitive group to variations in weather conditions, and their responses are quite similar across the public transit service area. Morning peak hours are the period when passengers have the strongest weather tolerance. Spatial heterogeneity of weather effects mainly occurs in adult, child, and tertiary student passengers, not seniors and secondary student passengers. In contrast to suburban areas, city centres and university campuses are the locales most likely to have distinct weather responses. The results suggest that it is important for transit operators to understand the spatiotemporal dynamics of the weather-transit ridership relationship to proactively (re)design and adjust scheduling to achieve weather-resilient performance.

Language: en

Keywords

Geographically weighted negative binomial regression; Local weather condition; Spatial heterogeneity; Transit smart card data