The University of Southampton
University of Southampton Institutional Repository

Dynamic population mapping using mobile phone data

Dynamic population mapping using mobile phone data
Dynamic population mapping using mobile phone data
During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.
0027-8424
15888-15893
Deville, P.
e13cc888-49ba-4af7-b3d6-8623f996eb4e
Linard, C.
40dc396f-bbf0-4ae2-8732-7a73447a9100
Martin, S.
638d43ca-2c18-49a1-886c-8cc4252361e0
Gilbert, M.
1783ad6f-c32e-46dd-8de0-eb0e139afce0
Stevens, F.R.
83fd6663-d8f2-4db5-bc71-c7961dc5218e
Gaughan, A.E.
46808c1b-4c19-4342-b628-8ad7251d9f90
Blondel, V.D.
7d6e866e-1ce6-4407-93f2-c9d40f745c41
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Deville, P.
e13cc888-49ba-4af7-b3d6-8623f996eb4e
Linard, C.
40dc396f-bbf0-4ae2-8732-7a73447a9100
Martin, S.
638d43ca-2c18-49a1-886c-8cc4252361e0
Gilbert, M.
1783ad6f-c32e-46dd-8de0-eb0e139afce0
Stevens, F.R.
83fd6663-d8f2-4db5-bc71-c7961dc5218e
Gaughan, A.E.
46808c1b-4c19-4342-b628-8ad7251d9f90
Blondel, V.D.
7d6e866e-1ce6-4407-93f2-c9d40f745c41
Tatem, A.J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F.R., Gaughan, A.E., Blondel, V.D. and Tatem, A.J. (2014) Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences, 111 (45), 15888-15893. (doi:10.1073/pnas.1408439111).

Record type: Article

Abstract

During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.

This record has no associated files available for download.

More information

Accepted/In Press date: 15 September 2014
e-pub ahead of print date: 27 October 2014
Published date: 11 November 2014
Organisations: Global Env Change & Earth Observation, WorldPop, Geography & Environment, Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 370705
URI: http://eprints.soton.ac.uk/id/eprint/370705
ISSN: 0027-8424
PURE UUID: a48e6731-d4e9-4156-ad89-b79ac0fe8b8f
ORCID for A.J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 04 Nov 2014 11:52
Last modified: 15 Mar 2024 03:43

Export record

Altmetrics

Contributors

Author: P. Deville
Author: C. Linard
Author: S. Martin
Author: M. Gilbert
Author: F.R. Stevens
Author: A.E. Gaughan
Author: V.D. Blondel
Author: A.J. Tatem ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×