Uncovering urban mobility patterns and impact of spatial distribution of places on movements

Wang Chen (), Qiang Gao and Hua-Gang Xiong ()
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Wang Chen: School of Electronic and Information Engineering, Beihang University, Beijing 100191, People’s Republic of China
Qiang Gao: School of Electronic and Information Engineering, Beihang University, Beijing 100191, People’s Republic of China
Hua-Gang Xiong: School of Electronic and Information Engineering, Beihang University, Beijing 100191, People’s Republic of China

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 01, 1-16

Abstract: As an important component in varieties of practical applications, understanding human urban mobility patterns draws intensive attention from researchers. In this paper, we investigate the urban mobility patterns and the impact of spatial distribution of places on the patterns using the data from a popular location-based social network Whrrl which are unrestricted to transportation modes. A movement region is demarcated for each city, which better depicts the concentrated active area of residents in the city than the administrative region. We show that the trip lengths in urban areas follow the exponential law unlike the power law in large scale of space. We find that the cities with larger sizes of place distribution area generally have smaller exponents of trip length distribution, larger means and deviations of trip lengths, while there are no apparent relationships between place densities and trip lengths. To examine the findings, we construct series of synthetic cities based on the power-law decay of place density and simulate urban human movement by the rank-based model. The simulations validate our findings and imply that the exponential distribution of urban trips is a combined result of power-law decay of place density and rank-based mobility preference.

Keywords: Human urban mobility; aggregated trip length; spatial place distribution; location-based social network (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0129183117500048

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