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Comparing Regional Patterns of Individual Movement Using Corrected Mobility Entropy

Lookup NU author(s): Maarten Vanhoof, Dr Thomas Ploetz

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group In this paper, we propose a correction of the Mobility Entropy indicator (ME) used to describe the diversity of individual movement patterns as can be captured by data from mobile phones. We argue that a correction is necessary because standard calculations of ME show a structural dependency on the geographical density of observation points, rendering results biased and comparisons between regions incorrect. As a solution, we propose the Corrected Mobility Entropy (CME). We apply our solution to a French mobile phone dataset with ∼18.5 million users. Results show CME to be less correlated to cell-tower density (r = –0.17 instead of –0.59 for ME). As a spatial pattern of mobility diversity, we find CME values to be higher in suburban regions compared to their related urban centers, while both decrease considerably with lowering urban center sizes. Based on regression models, we find mobility diversity to relate to factors like income and employment. Additionally, using CME reveals the role of car use in relation to land use, which was not recognized when using ME values. Our solution enables a better description of individual mobility at a large scale, which has applications in official statistics, urban planning and policy, and mobility research.


Publication metadata

Author(s): Vanhoof M, Schoors W, Van Rompaey A, Ploetz T, Smoreda Z

Publication type: Article

Publication status: Published

Journal: Journal of Urban Technology

Year: 2018

Volume: 25

Issue: 2

Pages: 27-61

Print publication date: 02/04/2018

Online publication date: 04/06/2018

Acceptance date: 02/04/2018

Date deposited: 27/06/2018

ISSN (print): 1063-0732

ISSN (electronic): 1466-1853

Publisher: Routledge

URL: https://doi.org/10.1080/10630732.2018.1450593

DOI: 10.1080/10630732.2018.1450593

Data Source Location: https://doi.org/10.17634/154300-80


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