Supersampling and network reconstruction of urban mobility

Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically on...

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Detalles Bibliográficos
Autores: Sagarra Pascual, Oleguer Josep, Szell, Michael, Santi, Paolo, Díaz Guilera, Albert, Ratti, Carlo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/104350
Acceso en línea:https://hdl.handle.net/2445/104350
Access Level:acceso abierto
Palabra clave:Entropia
Mobilitat social
Urbanisme
Variables aleatòries
Sistema de posicionament global
Entropy
Social mobility
City planning
Random variables
Global Positioning System
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spelling Supersampling and network reconstruction of urban mobilitySagarra Pascual, Oleguer JosepSzell, MichaelSanti, PaoloDíaz Guilera, AlbertRatti, CarloEntropiaMobilitat socialUrbanismeVariables aleatòriesSistema de posicionament globalEntropySocial mobilityCity planningRandom variablesGlobal Positioning SystemUnderstanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture of the entire system under study. Methods to reliably extract mobility information from such reduced data and to assess their sampling biases are lacking. To that end, we analyzed a data set of millions of taxi movements in New York City. We first show that, once they are appropriately transformed, mobility patterns are highly stable over long time scales. Based on this observation, we develop a supersampling methodology to reliably extrapolate mobility records from a reduced sample based on an entropy maximization procedure, and we propose a number of network-based metrics to assess the accuracy of the predicted vehicle flows. Our approach provides a well founded way to exploit temporal patterns to save effort in recording mobility data, and opens the possibility to scale up data from limited records when information on the full system is required.Public Library of Science (PLoS)2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/104350Articles publicats en revistes (Física de la Matèria Condensada)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1371/journal.pone.0134508PLoS One, 2015, vol. 10, num. 8, p. e0134508https://doi.org/10.1371/journal.pone.0134508info:eu-repo/grantAgreement/EC/FP7/318132cc-by (c) Sagarra Pascual, Oleguer Josep et al., 2015http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1043502026-05-27T06:46:51Z
dc.title.none.fl_str_mv Supersampling and network reconstruction of urban mobility
title Supersampling and network reconstruction of urban mobility
spellingShingle Supersampling and network reconstruction of urban mobility
Sagarra Pascual, Oleguer Josep
Entropia
Mobilitat social
Urbanisme
Variables aleatòries
Sistema de posicionament global
Entropy
Social mobility
City planning
Random variables
Global Positioning System
title_short Supersampling and network reconstruction of urban mobility
title_full Supersampling and network reconstruction of urban mobility
title_fullStr Supersampling and network reconstruction of urban mobility
title_full_unstemmed Supersampling and network reconstruction of urban mobility
title_sort Supersampling and network reconstruction of urban mobility
dc.creator.none.fl_str_mv Sagarra Pascual, Oleguer Josep
Szell, Michael
Santi, Paolo
Díaz Guilera, Albert
Ratti, Carlo
author Sagarra Pascual, Oleguer Josep
author_facet Sagarra Pascual, Oleguer Josep
Szell, Michael
Santi, Paolo
Díaz Guilera, Albert
Ratti, Carlo
author_role author
author2 Szell, Michael
Santi, Paolo
Díaz Guilera, Albert
Ratti, Carlo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Entropia
Mobilitat social
Urbanisme
Variables aleatòries
Sistema de posicionament global
Entropy
Social mobility
City planning
Random variables
Global Positioning System
topic Entropia
Mobilitat social
Urbanisme
Variables aleatòries
Sistema de posicionament global
Entropy
Social mobility
City planning
Random variables
Global Positioning System
description Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture of the entire system under study. Methods to reliably extract mobility information from such reduced data and to assess their sampling biases are lacking. To that end, we analyzed a data set of millions of taxi movements in New York City. We first show that, once they are appropriately transformed, mobility patterns are highly stable over long time scales. Based on this observation, we develop a supersampling methodology to reliably extrapolate mobility records from a reduced sample based on an entropy maximization procedure, and we propose a number of network-based metrics to assess the accuracy of the predicted vehicle flows. Our approach provides a well founded way to exploit temporal patterns to save effort in recording mobility data, and opens the possibility to scale up data from limited records when information on the full system is required.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/104350
url https://hdl.handle.net/2445/104350
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1371/journal.pone.0134508
PLoS One, 2015, vol. 10, num. 8, p. e0134508
https://doi.org/10.1371/journal.pone.0134508
info:eu-repo/grantAgreement/EC/FP7/318132
dc.rights.none.fl_str_mv cc-by (c) Sagarra Pascual, Oleguer Josep et al., 2015
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Sagarra Pascual, Oleguer Josep et al., 2015
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library of Science (PLoS)
publisher.none.fl_str_mv Public Library of Science (PLoS)
dc.source.none.fl_str_mv Articles publicats en revistes (Física de la Matèria Condensada)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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