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Identifying seasonal mobility profiles from anonymized and aggregated mobile phone data. Application in food security

Author

Listed:
  • Pedro J Zufiria
  • David Pastor-Escuredo
  • Luis Úbeda-Medina
  • Miguel A Hernandez-Medina
  • Iker Barriales-Valbuena
  • Alfredo J Morales
  • Damien C Jacques
  • Wilfred Nkwambi
  • M Bamba Diop
  • John Quinn
  • Paula Hidalgo-Sanchís
  • Miguel Luengo-Oroz

Abstract

We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale population count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.

Suggested Citation

  • Pedro J Zufiria & David Pastor-Escuredo & Luis Úbeda-Medina & Miguel A Hernandez-Medina & Iker Barriales-Valbuena & Alfredo J Morales & Damien C Jacques & Wilfred Nkwambi & M Bamba Diop & John Quinn &, 2018. "Identifying seasonal mobility profiles from anonymized and aggregated mobile phone data. Application in food security," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-20, April.
  • Handle: RePEc:plo:pone00:0195714
    DOI: 10.1371/journal.pone.0195714
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    References listed on IDEAS

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    1. Ennio Cascetta & Domenico Inaudi & Gérald Marquis, 1993. "Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts," Transportation Science, INFORMS, vol. 27(4), pages 363-373, November.
    2. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
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    Cited by:

    1. D. Woods & A. Cunningham & C. E. Utazi & M. Bondarenko & L. Shengjie & G. E. Rogers & P. Koper & C. W. Ruktanonchai & E. zu Erbach-Schoenberg & A. J. Tatem & J. Steele & A. Sorichetta, 2022. "Exploring methods for mapping seasonal population changes using mobile phone data," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-17, December.
    2. David Pastor-Escuredo & Yolanda Torres & María Martínez-Torres & Pedro J. Zufiria, 2020. "Rapid Multi-Dimensional Impact Assessment of Floods," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
    3. David Pastor-Escuredo, 2021. "Future of work: ethics," Papers 2104.02580, arXiv.org.
    4. David Pastor-Escuredo & Philip Treleaven, 2021. "Multiscale Governance," Papers 2104.02752, arXiv.org.

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