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Modelling and analysing effects of complex seasonality and weather on an area's daily transit ridership rate

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  • Kashfi, Syeed Anta
  • Bunker, Jonathan M.
  • Yigitcanlar, Tan

Abstract

Adverse weather is generally perceived as deterrent for public transit uses. This has also been highlighted in previous literatures. In contrary, our previous study found no association between weather and transit ridership while investigating the underlying temporal influences behind variation in daily ridership across the sub-tropical city of Brisbane, Australia. This contraindication led to the primary focus of this research. This research acknowledged that Inclusion of weather variables in conjunction with other relatively strong independent variables might result in washout of the weather effects on ridership. Variables such as rainfall do not recur on a daily basis throughout the year. Thus, generalising their effect on ridership with other independent variables that consistently influence ridership may create a similar problem. Hence, weather variables were converted into their normalised factors and combined with other independent variables while formulated the optimised the daily ridership rate estimation model. Several models were developed concerning various combinations of weather variables and through rigorous analysis it was identified that only the rain variable has noticeable effect on daily ridership. Evidently, this study functions as an update of our former study by directing towards a new approach to the analysis of the relationship between weather and transit ridership.

Suggested Citation

  • Kashfi, Syeed Anta & Bunker, Jonathan M. & Yigitcanlar, Tan, 2016. "Modelling and analysing effects of complex seasonality and weather on an area's daily transit ridership rate," Journal of Transport Geography, Elsevier, vol. 54(C), pages 310-324.
  • Handle: RePEc:eee:jotrge:v:54:y:2016:i:c:p:310-324
    DOI: 10.1016/j.jtrangeo.2016.06.018
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    References listed on IDEAS

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    Cited by:

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    2. Zhao, Jinbao & Wang, Jian & Xing, Zhaomin & Luan, Xin & Jiang, Yang, 2018. "Weather and cycling: Mining big data to have an in-depth understanding of the association of weather variability with cycling on an off-road trail and an on-road bike lane," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 119-135.
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    5. Zhou, Yufeng & Li, Zihao & Meng, Yangyang & Li, Zhongwen & Zhong, Maohua, 2021. "Analyzing spatio-temporal impacts of extreme rainfall events on metro ridership characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    6. Yang, Xiaobao & Yue, Xianfei & Sun, Huijun & Gao, Ziyou & Wang, Wencheng, 2021. "Impact of weather on freeway origin-destination volume in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 143(C), pages 30-47.
    7. Liping Ge & Malek Sarhani & Stefan Voß & Lin Xie, 2021. "Review of Transit Data Sources: Potentials, Challenges and Complementarity," Sustainability, MDPI, vol. 13(20), pages 1-37, October.
    8. Kevin Lanza & Casey P. Durand, 2021. "Heat-Moderating Effects of Bus Stop Shelters and Tree Shade on Public Transport Ridership," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    9. Wei, Ming & Liu, Yan & Sigler, Thomas & Liu, Xiaoyang & Corcoran, Jonathan, 2019. "The influence of weather conditions on adult transit ridership in the sub-tropics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 106-118.

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