Multi-scale spatio-temporal analysis of human mobility.

Laura Alessandretti, Piotr Sapiezynski, Sune Lehmann, Andrea Baronchelli
Author Information
  1. Laura Alessandretti: City, University of London, London EC1V 0HB, United Kingdom.
  2. Piotr Sapiezynski: Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.
  3. Sune Lehmann: Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.
  4. Andrea Baronchelli: City, University of London, London EC1V 0HB, United Kingdom.

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.

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MeSH Term

Algorithms
Humans
Models, Theoretical
Motor Activity
Spatio-Temporal Analysis
Time Factors

Word Cloud

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