Work

Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata

Year: 2018

Type: article

Abstract: 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.

Source: IEEE Transactions on Mobile Computing

DOI: 10.1109/tmc.2018.2871156

Authors: Ghazaleh Khodabandelou, Vincent Gauthier, Marco Fiore, Mounim A. El-Yacoubi

Institutions: Centre National de la Recherche Scientifique, Université Paris-Saclay, National Research Council

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: green

Funder: Bpifrance