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Human mobility and socioeconomic datasets of the Rio de Janeiro metropolitan area.
Chaves, Júlio César; da Silva, Moacyr A H B; Alencar, Ricardo de Souza; Evsukoff, Alexandre G; Vieira, Vinícius da Fonseca.
Afiliación
  • Chaves JC; EMAp/Getulio Vargas Foundation, Praia de Botafogo 190, Botafogo, 22253-900, Rio de Janeiro, Brazil.
  • da Silva MAHB; EMAp/Getulio Vargas Foundation, Praia de Botafogo 190, Botafogo, 22253-900, Rio de Janeiro, Brazil.
  • Alencar RS; Coppe/Federal University of Rio de Janeiro, 68506, Rio de Janeiro, Brazil.
  • Evsukoff AG; Coppe/Federal University of Rio de Janeiro, 68506, Rio de Janeiro, Brazil.
  • Vieira VDF; Universidade Federal de São João del Rei, Praça Frei Orlando, 170, 36307-352, São João del Rei, Brazil.
Data Brief ; 51: 109695, 2023 Dec.
Article en En | MEDLINE | ID: mdl-37965603
This data descriptor presents two main datasets and a set of auxiliary files. The mobility dataset presents a long-term study of human mobility in the Rio de Janeiro Metropolitan Area (RJMA) performed in the entire year of 2014 based on mobile phone data. The socioeconomic dataset presents selected socioeconomic variables of the Brazilian 2010 census. A set of auxiliary files is included to present georeferenced information and geographic features (shapefiles) and data used to validate the mobility estimates. The human mobility estimation was carried out using a methodology that allows direct integration with census data, based on an approximation of the geographic boundaries of census units by an aggregation of Voronoi polygons of the mobile phone antennas. The study area is the Brazilian local area 21, which includes the entire RJMA and four other municipalities. The mobility dataset is divided into two files: one is an estimation of the origin-destination (OD) matrix per day, and the other is a visitors' dataset where the number of visitors of each location is estimated in four shifts each day. The socioeconomic dataset presents information of 55 variables for each location, which have been used in different studies and present the longest human mobility dataset available for public use.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2023 Tipo del documento: Article País de afiliación: Brasil

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2023 Tipo del documento: Article País de afiliación: Brasil