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Article Dans Une Revue IEEE Transactions on Mobile Computing Année : 2019

Estimation of static and dynamic urban populations with mobile network metadata

Résumé

Communication-enabled devices routinely carried by individuals have become pervasive, opening unprecedented opportunities for collecting digital metadata about the mobility of large populations. In this paper, we propose a novel methodology for the estimation of people density at metropolitan scales, using subscriber presence metadata collected by a mobile operator. Our approach suits the estimation of static population densities, i.e., of the distribution of dwelling units per urban area contained in traditional censuses. More importantly, it enables the estimation of dynamic population densities, i.e., the time-varying distributions of people in a conurbation. By leveraging substantial real-world mobile network metadata and ground-truth information, we demonstrate that the accuracy of our solution is superior to that granted by state-of-the-art methods in practical heterogeneous urban scenarios.
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Dates et versions

hal-02286129 , version 1 (13-09-2019)

Identifiants

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Ghazaleh Khodabandelou, Vincent Gauthier, Marco Fiore, Mounim El Yacoubi. Estimation of static and dynamic urban populations with mobile network metadata. IEEE Transactions on Mobile Computing, 2019, 18 (9), pp.2034-2047. ⟨10.1109/TMC.2018.2871156⟩. ⟨hal-02286129⟩
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