Analysing the relationship between weather, built environment, and public transport ridership

Abstract

For a sustainable public transport system, it is important to unveil the spatiotemporal characteristics of ridership and identify the influence mechanisms. Some studies analysed the effects of weather and built environment separately, however, their effects when incorporated remains to be determined. Using smart card data, weather information, and point of interest data from Beijing, the Light Gradient Boosted Machine was employed to investigate the relative importance of weather and built environment variables contributing to daily ridership at the traffic analysis zone level, and investigate the non-linear relationship and interaction effects between them. Weather conditions and built environment contribute 30.22 and 55.83% to ridership fluctuations, respectively. Most variables show complex non-linear and threshold effects on ridership. The interaction effects of weather and weekend/public holiday have a more substantial influence on ridership than weekdays, indicating weather conditions have less impact on regular commuting trips than discretionary trips. The ridership fluctuations in response to changing weather conditions vary with spatial locations. Adverse weather, such as strong wind, high humidity, or heavy rainfall, has a more disruptive impact on leisure-related areas than on residence and office areas. This study can benefit stakeholders in making decisions about optimising public transport networks and scheduling service frequency. 2 Literature review 2.1 Impact of weather conditions Many previous studies have addressed the effects of rain, temperature, and wind on public transport ridership. Generally, extreme weather conditions, such as very high and low temperatures, strong wind, and heavy precipitation, reduce public transport ridership [14-17]. However, the effect of weather

Examining Built Environment Effects on Metro Ridership at Station-to-Station Level considering Circle Heterogeneity: A Case Study from Xi’an, China

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Extreme Weather Influence on Carbon Emissions in Chinese Urban Traffic Environments

“…These areas include the central and marginal areas (Lianhu District, Yanta District, Weiyang District, Chang'an District, and Lintong District), which can represent different urban spatial structures. Moreover, the residents' transportation preferences across the different regions also have their own characteristics (Lin et al, 2020). Taking into account the time when extreme weather is prone to occur, the investigation was carried out from November 15, 2016 to March 15, 2017 (city heating), from June 1, 2017 to August 30, 2017 (summer), and from December 1, 2016 to February 28, 2017 (winter).…”

“…The changing characteristics of carbon dioxide emissions from urban commuters will be a key feature of future climate change scenarios and an important field of focus for researchers and policymakers. Some scholars have long been concerned about the impact of weather change on commuter travel behavior and has conducted a series of studies on this issue (de Kuijf et al, 2021; Lin et al, 2020; C. Q. Liu et al, 2015a, 2015b, 2015c).…”

Non-Linear Effects of the Built Environment and Social Environment on Bus Use among Older Adults in China: An Application of the XGBoost Model

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