Human mobility and socioeconomic datasets of the Rio de Janeiro metropolitan area

Júlio César Chaves; Moacyr A H B da Silva; Ricardo de Souza Alencar; Alexandre G Evsukoff; Vinícius da Fonseca Vieira

doi:10.1016/j.dib.2023.109695

Human mobility and socioeconomic datasets of the Rio de Janeiro metropolitan area

Data Brief. 2023 Oct 18:51:109695. doi: 10.1016/j.dib.2023.109695. eCollection 2023 Dec.

Authors

Júlio César Chaves¹, Moacyr A H B da Silva¹, Ricardo de Souza Alencar², Alexandre G Evsukoff², Vinícius da Fonseca Vieira³

Affiliations

¹ EMAp/Getulio Vargas Foundation, Praia de Botafogo 190, Botafogo, 22253-900, Rio de Janeiro, Brazil.
² Coppe/Federal University of Rio de Janeiro, 68506, Rio de Janeiro, Brazil.
³ Universidade Federal de São João del Rei, Praça Frei Orlando, 170, 36307-352, São João del Rei, Brazil.

Abstract

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.

Keywords: Call detail records; Human mobility; Mobile phone data; Rio de janeiro metropolitan area; Socioeconomic indicators; Transportation planning.