Metropolitan Migratory Trends in the Post‐Pandemic Context. Analysis of the Madrid Region Based on Mobile Phone Network Data
| dc.contributor.author | Marigil Alba, Carlos | |
| dc.contributor.author | Romanillos Arroyo, Gustavo | |
| dc.contributor.author | García Palomares, Juan Carlos | |
| dc.contributor.author | Sánchez Cauce, Raquel | |
| dc.date.accessioned | 2025-11-20T06:52:57Z | |
| dc.date.available | 2025-11-20T06:52:57Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This paper aims to enrich the current literature on the study of migratory movements in the context of COVID‐19 and the post‐ pandemic period. While most of the studies on this topic measure migration using official registers, we propose a new methodology based on the leverage of mobile phone network data, taken from the Madrid region, as a case study. While the use of such data are common in other fields, such as transport and mobility planning, we demonstrate their usefulness in the study of migration. Analysing the case of Madrid, we find new evidence of the changes in migratory trends during COVID‐19, of increased immigration into rural and outer suburban areas and emigration from core urban areas. A geographical description of the new migration trends is provided on different scales (from the national to the metropolitan and municipal scale, including small urban transportation zones), and by socioeconomic group. In addition, we provide some ideas about these trends in the post‐pandemic context, as the evolution of migratory trends varies for different groups. | |
| dc.description.department | Depto. de Geografía | |
| dc.description.faculty | Fac. de Geografía e Historia | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | MICIU/AEI/10.13039/501100011033/ and ‘European Union NextGenerationEU/PRTR’ | |
| dc.description.status | pub | |
| dc.identifier.citation | Marigil‐Alba, Carlos, et al. «Metropolitan Migratory Trends in the Post‐Pandemic Context. Analysis of the Madrid Region Based on Mobile Phone Network Data». Population, Space and Place, vol. 31, n.o 3, abril de 2025, p. e70017. DOI.org (Crossref), https://doi.org/10.1002/psp.70017. | |
| dc.identifier.doi | 10.1002/psp.70017 | |
| dc.identifier.officialurl | https://doi.org/10.1002/psp.70017 | |
| dc.identifier.relatedurl | https://onlinelibrary.wiley.com/doi/10.1002/psp.70017 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/126269 | |
| dc.issue.number | 3 | |
| dc.journal.title | Population, Space and Place | |
| dc.language.iso | eng | |
| dc.publisher | Wiley | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PCI2020-120706-2/ES/DEEP LEARNING ANTICIPATED URBAN MOBILITY PEAKS/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116656RB-I00/ES/EVALUACION, ANALISIS Y PREDICCION DE LOS CAMBIOS EN LA MOVILIDAD URBANA TRAS LA PANDEMIA A PARTIR DE BIG DATA GEOLOCALIZADO/ | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.keyword | COVID‐19 | |
| dc.subject.keyword | Madrid | |
| dc.subject.keyword | Metropolitan areas | |
| dc.subject.keyword | Mobile phone network data | |
| dc.subject.keyword | Residential migration | |
| dc.subject.ucm | Ciencias Sociales | |
| dc.subject.ucm | Geografía humana | |
| dc.subject.ucm | Sistemas de información geográfica | |
| dc.subject.unesco | 54 Geografía | |
| dc.title | Metropolitan Migratory Trends in the Post‐Pandemic Context. Analysis of the Madrid Region Based on Mobile Phone Network Data | |
| dc.type | journal article | |
| dc.volume.number | 31 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 7af12201-dd9c-4deb-8f3e-16bacc43e6dd | |
| relation.isAuthorOfPublication | b25b5524-305e-4aa0-a30e-5b15a398806c | |
| relation.isAuthorOfPublication.latestForDiscovery | 7af12201-dd9c-4deb-8f3e-16bacc43e6dd |
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