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Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data

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  • Bi Yu Chen
  • Yafei Wang
  • Donggen Wang
  • Qingquan Li
  • William H. K. Lam
  • Shih-Lung Shaw

Abstract

Many existing accessibility studies ignore human mobility due to the lack of large-scale human mobility data. This study investigates the impacts of human mobility on accessibility using massive mobile phone tracking data collected in Shenzhen, China. In this study, human mobility information is extracted from mobile phone tracking data using a time-geographic approach. The accessibility of each phone user is evaluated using fine spatial resolution across the entire city. The impacts of human mobility on accessibility are quantified by using relative accessibility ratios between phone users and a virtual stationary user in the same residential location. Results of this study enrich understandings of how land use influences relationships between human mobility and accessibility. For resource-poor regions with sparse service facilities, human mobility can greatly enhance individual accessibility. In contrast, for resource-rich regions with dense service facilities, human mobility can even reduce individual accessibility. Overall, human mobility can reduce spatial inequity of accessibility for people living in different regions of the city. The results of this study also have several important methodological implications for including human mobility and time dimension in accessibility evaluations.

Suggested Citation

  • Bi Yu Chen & Yafei Wang & Donggen Wang & Qingquan Li & William H. K. Lam & Shih-Lung Shaw, 2018. "Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(4), pages 1115-1133, July.
    • Handle: RePEc:taf:raagxx:v:108:y:2018:i:4:p:1115-1133
    DOI: 10.1080/24694452.2017.1411244
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    Cited by:

    1. Zijing Ye & Ruisi Li & Jing Wu, 2022. "Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    2. Marina Toger & Karima Kourtit & Peter Nijkamp & John Östh, 2021. "Mobility during the COVID-19 Pandemic: A Data-Driven Time-Geographic Analysis of Health-Induced Mobility Changes," Sustainability, MDPI, vol. 13(7), pages 1-21, April.
    3. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    4. Tianren Yang & Ying Jin & Longxu Yan & Pei Pei, 2019. "Aspirations and realities of polycentric development: Insights from multi-source data into the emerging urban form of Shanghai," Environment and Planning B, , vol. 46(7), pages 1264-1280, September.
    5. Gang Cheng & Leishan Guo & Tao Zhang, 2022. "Spatial Equity Assessment of Bus Travel Behavior for Pilgrimage: Evidence from Lhasa, Tibet, China," Sustainability, MDPI, vol. 14(17), pages 1-15, August.
    6. Zuo, Yufan & Fu, Xiao & Liu, Zhiyuan & Huang, Di, 2021. "Short-term forecasts on individual accessibility in bus system based on neural network model," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. Li, Teng & Barwick, Panle Jia & Deng, Yongheng & Huang, Xinfei & Li, Shanjun, 2023. "The COVID-19 pandemic and unemployment: Evidence from mobile phone data from China," Journal of Urban Economics, Elsevier, vol. 135(C).
    8. Wang, Yafei & Chen, Bi Yu & Yuan, Hui & Wang, Donggen & Lam, William H.K. & Li, Qingquan, 2018. "Measuring temporal variation of location-based accessibility using space-time utility perspective," Journal of Transport Geography, Elsevier, vol. 73(C), pages 13-24.
    9. Chen, Bi Yu & Cheng, Xue-Ping & Kwan, Mei-Po & Schwanen, Tim, 2020. "Evaluating spatial accessibility to healthcare services under travel time uncertainty: A reliability-based floating catchment area approach," Journal of Transport Geography, Elsevier, vol. 87(C).

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