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Multi-scale spatio-temporal analysis of human mobility

Author

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  • Laura Alessandretti
  • Piotr Sapiezynski
  • Sune Lehmann
  • Andrea Baronchelli

Abstract

The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals’ digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life.

Suggested Citation

  • Laura Alessandretti & Piotr Sapiezynski & Sune Lehmann & Andrea Baronchelli, 2017. "Multi-scale spatio-temporal analysis of human mobility," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-17, February.
    • Handle: RePEc:plo:pone00:0171686
    DOI: 10.1371/journal.pone.0171686
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    References listed on IDEAS

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    Cited by:

    1. Masahiko Haraguchi & Akihiko Nishino & Akira Kodaka & Maura Allaire & Upmanu Lall & Liao Kuei-Hsien & Kaya Onda & Kota Tsubouchi & Naohiko Kohtake, 2022. "Human mobility data and analysis for urban resilience: A systematic review," Environment and Planning B, , vol. 49(5), pages 1507-1535, June.
    2. Rutten, Philip & Lees, Michael H. & Klous, Sander & Sloot, Peter M.A., 2021. "Intermittent and persistent movement patterns of dance event visitors in large sporting venues," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Fan Yang & Zhenxing Yao & Fan Ding & Huachun Tan & Bin Ran, 2019. "Understanding Urban Mobility Pattern with Cellular Phone Data: A Case Study of Residents and Travelers in Nanjing," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    4. Hengfang Deng & Daniel P. Aldrich & Michael M. Danziger & Jianxi Gao & Nolan E. Phillips & Sean P. Cornelius & Qi Ryan Wang, 2021. "High-resolution human mobility data reveal race and wealth disparities in disaster evacuation patterns," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-8, December.
    5. Laura Alessandretti & Luis Guillermo Natera Orozco & Meead Saberi & Michael Szell & Federico Battiston, 2023. "Multimodal urban mobility and multilayer transport networks," Environment and Planning B, , vol. 50(8), pages 2038-2070, October.

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