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Exploring spatial variation of the bus stop influence zone with multi-source data: A case study in Zhenjiang, China

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  • Pan, Yingjiu
  • Chen, Shuyan
  • Li, Tiezhu
  • Niu, Shifeng
  • Tang, Kun

Abstract

Bus stops are important traffic facilities that affect the efficiency of transportation system as well as the characteristics of bus emissions, and the bus stop influence zone (BSIZ) is the basic to estimate the bus emissions. The primary objective of this study is to investigate how the potential factors affect the length of BSIZ. In this study, the geographically weighted regression (GWR) model was implemented to build a relationship between the length of BSIZ and various contributing factors. The spatial heterogeneity of the length of BSIZ was explored, and the spatial distributions of parameter estimations were visualized. Five types of data including bus emission data, global positioning system (GPS) data, point of interest (POI) data, bus stop feature data, and road feature data were collected from Zhenjiang in China to illustrate the procedure. The results indicated that the urban form has a significant impact on the length of BSIZ, and strong spatial variability for the length of BSIZ is observed. The number of enterprises and companies around bus stops, the distance between the stop and intersection, road hierarchy, the number of public facilities, the queue length of buses, as well as traffic volume can significantly affect the length of BSIZ, and the estimated coefficients of each bus stop vary across regions. The results provided valuable insights which contribute to quantify and estimate the emissions generated near bus stops.

Suggested Citation

  • Pan, Yingjiu & Chen, Shuyan & Li, Tiezhu & Niu, Shifeng & Tang, Kun, 2019. "Exploring spatial variation of the bus stop influence zone with multi-source data: A case study in Zhenjiang, China," Journal of Transport Geography, Elsevier, vol. 76(C), pages 166-177.
    • Handle: RePEc:eee:jotrge:v:76:y:2019:i:c:p:166-177
    DOI: 10.1016/j.jtrangeo.2019.03.012
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    References listed on IDEAS

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    1. Yanjie Ji & Xinwei Ma & Mingyuan Yang & Yuchuan Jin & Liangpeng Gao, 2018. "Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
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    Cited by:

    1. Huang, Ying & Xu, Wangtu (Ato), 2021. "Spatial and temporal heterogeneity of the impact of high-speed railway on urban economy: Empirical study of Chinese cities," Journal of Transport Geography, Elsevier, vol. 91(C).
    2. Weixi Ren & Bo Yu & Yuren Chen & Kun Gao, 2022. "Divergent Effects of Factors on Crash Severity under Autonomous and Conventional Driving Modes Using a Hierarchical Bayesian Approach," IJERPH, MDPI, vol. 19(18), pages 1-22, September.
    3. Wenzhu Zhou & Yiwen Zhang & Yajun Tang, 2023. "Spatiotemporal Evolution and Mechanisms of Polder Land Use in the “Water-Polder-Village” System: A Case Study of Gaochun District in Nanjing, China," Land, MDPI, vol. 12(9), pages 1-21, September.
    4. Yang, Binyu & Tian, Yuan & Wang, Jian & Hu, Xiaowei & An, Shi, 2022. "How to improve urban transportation planning in big data era? A practice in the study of traffic analysis zone delineation," Transport Policy, Elsevier, vol. 127(C), pages 1-14.
    5. Qian Yu & Lili Lu & Tiezhu Li & Ran Tu, 2022. "Quantifying the Impact of Alternative Bus Stop Platforms on Vehicle Emissions and Individual Pollution Exposure at Bus Stops," IJERPH, MDPI, vol. 19(11), pages 1-16, May.
    6. Junxiang Zhang & Bo Yu & Yuren Chen & You Kong & Jianqiang Gao, 2022. "Comparative Analysis of Influencing Factors on Crash Severity between Super Multi-Lane and Traditional Multi-Lane Freeways Considering Spatial Heterogeneity," IJERPH, MDPI, vol. 19(19), pages 1-15, October.
    7. Jin, Mengjie & Gu, Ruyue & Li, Kevin X. & Shi, Wenming & Xiao, Yi, 2024. "Heterogeneous impacts of the high-speed railway network on urban–rural income disparity: Spatiotemporal evidence from Yangtze River Delta of China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    8. Xingchen Yan & Tao Wang & Jun Chen & Xiaofei Ye & Zhen Yang & Hua Bai, 2019. "Analysis of the Characteristics and Number of Bicycle–Passenger Conflicts at Bus Stops for Improving Safety," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    9. Pan, Yingjiu & Chen, Shuyan & Niu, Shifeng & Ma, Yongfeng & Tang, Kun, 2020. "Investigating the impacts of built environment on traffic states incorporating spatial heterogeneity," Journal of Transport Geography, Elsevier, vol. 83(C).

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