Measuring spatial subdivisions in urban mobility with mobile phone data
| dc.contributor.author | Graells Garrido, Eduardo |
| dc.contributor.author | Meta, Irene |
| dc.contributor.author | Serra Burriel, Feliu |
| dc.contributor.author | Reyes Valenzuela, Patricio Alejandro |
| dc.contributor.author | Cucchietti, Fernando |
| dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Estadística i Investigació Operativa |
| dc.contributor.other | Barcelona Supercomputing Center |
| dc.date.accessioned | 2021-02-02T14:19:37Z |
| dc.date.available | 2021-02-02T14:19:37Z |
| dc.date.issued | 2020 |
| dc.description.abstract | Urban population grows constantly. By 2050 two thirds of the world population will reside in urban areas. This growth is faster and more complex than the ability of cities to measure and plan for their sustainability. To understand what makes a city inclusive for all, we define a methodology to identify and characterize spatial subdivisions: areas with over- and under-representation of specific population groups, named hot and cold spots respectively. Using aggregated mobile phone data, we apply this methodology to the city of Barcelona to assess the mobility of three groups of people: women, elders, and tourists. We find that, within the three groups, cold spots have a lower diversity of amenities and services than hot spots. Also, cold spots of women and tourists tend to have lower population income. These insights apply to the floating population of Barcelona, thus augmenting the scope of how inclusiveness can be analyzed in the city. |
| dc.description.peerreviewed | Peer Reviewed |
| dc.description.sponsorship | This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 857191 (IoTwins project). E. Graells-Garrido was partially funded by CONICYT Fondecyt de Iniciación project #11180913. |
| dc.description.version | Postprint (published version) |
| dc.format.extent | 10 p. |
| dc.identifier.citation | Graells, E. [et al.]. Measuring spatial subdivisions in urban mobility with mobile phone data. A: International World Wide Web Conference. "The Web Conference 2020, companion of The World Wide Web Conference, WWW 2020: April 20–24, 2020, Taipei, Taiwan". New York: Association for Computing Machinery (ACM), 2020, p. 485-494. ISBN 978-1-4503-7024-0. DOI 10.1145/3366424.3384370. |
| dc.identifier.doi | 10.1145/3366424.3384370 |
| dc.identifier.isbn | 978-1-4503-7024-0 |
| dc.identifier.uri | https://hdl.handle.net/2117/336719 |
| dc.language.iso | eng |
| dc.publisher | Association for Computing Machinery (ACM) |
| dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/857191/EU/Distributed Digital Twins for industrial SMEs: a big-data platform/IoTwins |
| dc.relation.publisherversion | https://dl.acm.org/doi/10.1145/3366424.3384370 |
| dc.rights.access | Open Access |
| dc.rights.licensename | Attribution 4.0 International |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ |
| dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Comunicacions mòbils |
| dc.subject.lcsh | Mobile computing |
| dc.subject.lcsh | Sustainable urban development |
| dc.subject.lemac | Informàtica mòbil |
| dc.subject.lemac | Desenvolupament urbà sostenible |
| dc.subject.other | Urban mobility |
| dc.subject.other | Mobile phone data |
| dc.subject.other | Spatial analysis |
| dc.title | Measuring spatial subdivisions in urban mobility with mobile phone data |
| dc.type | Conference report |
| dspace.entity.type | Publication |
| local.citation.author | Graells, E.; Meta, I.; Serra, F.; Reyes, P.; Cucchietti, F. |
| local.citation.contributor | International World Wide Web Conference |
| local.citation.endingPage | 494 |
| local.citation.publicationName | The Web Conference 2020, companion of The World Wide Web Conference, WWW 2020: April 20–24, 2020, Taipei, Taiwan |
| local.citation.pubplace | New York |
| local.citation.startingPage | 485 |
| local.identifier.drac | 30452350 |
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