The universal visitation law of human mobility

Markus Schläpfer, Lei Dong (), Kevin O’Keeffe, Paolo Santi, Michael Szell, Hadrien Salat, Samuel Anklesaria, Mohammad Vazifeh, Carlo Ratti and Geoffrey B. West
Additional contact information
Markus Schläpfer: Massachusetts Institute of Technology
Lei Dong: Massachusetts Institute of Technology
Kevin O’Keeffe: Massachusetts Institute of Technology
Paolo Santi: Massachusetts Institute of Technology
Michael Szell: Massachusetts Institute of Technology
Hadrien Salat: Singapore-ETH Centre, ETH Zurich
Samuel Anklesaria: Massachusetts Institute of Technology
Mohammad Vazifeh: Massachusetts Institute of Technology
Carlo Ratti: Massachusetts Institute of Technology
Geoffrey B. West: Santa Fe Institute

Nature, 2021, vol. 593, issue 7860, 522-527

Abstract: Abstract Human mobility impacts many aspects of a city, from its spatial structure1–3 to its response to an epidemic4–7. It is also ultimately key to social interactions8, innovation9,10 and productivity11. However, our quantitative understanding of the aggregate movements of individuals remains incomplete. Existing models—such as the gravity law12,13 or the radiation model14—concentrate on the purely spatial dependence of mobility flows and do not capture the varying frequencies of recurrent visits to the same locations. Here we reveal a simple and robust scaling law that captures the temporal and spatial spectrum of population movement on the basis of large-scale mobility data from diverse cities around the globe. According to this law, the number of visitors to any location decreases as the inverse square of the product of their visiting frequency and travel distance. We further show that the spatio-temporal flows to different locations give rise to prominent spatial clusters with an area distribution that follows Zipf’s law15. Finally, we build an individual mobility model based on exploration and preferential return to provide a mechanistic explanation for the discovered scaling law and the emerging spatial structure. Our findings corroborate long-standing conjectures in human geography (such as central place theory16 and Weber’s theory of emergent optimality10) and allow for predictions of recurrent flows, providing a basis for applications in urban planning, traffic engineering and the mitigation of epidemic diseases.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
https://www.nature.com/articles/s41586-021-03480-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:593:y:2021:i:7860:d:10.1038_s41586-021-03480-9

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-021-03480-9

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().