Entropy As a Measure of Attractiveness and Socioeconomic Complexity in Rio De Janeiro Metropolitan Area

Overview

Journal Entropy (Basel)

Publisher MDPI

Date 2020 Dec 8

PMID 33286142

Citations 5

Authors

Maxime Lenormand

Horacio Samaniego

Julio Cesar Chaves

Vinicius da Fonseca Vieira

Moacyr Alvim Horta Barbosa da Silva

Alexandre Goncalves Evsukoff

Affiliations

Soon will be listed here.

Abstract

Defining and measuring spatial inequalities across the urban environment remains a complex and elusive task which has been facilitated by the increasing availability of large geolocated databases. In this study, we rely on a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location in the Rio de Janeiro Metropolitan Area (Brazil) as the diversity of visitors' location of residence. The results show that the attractiveness of a given location measured by entropy is an important descriptor of the socioeconomic status of the location, and can thus be used as a proxy for complex socioeconomic indicators.

Citing Articles

Risk Index of Regional Infection Expansion of COVID-19: Moving Direction Entropy Study Using Mobility Data and Its Application to Tokyo.

Ohsawa Y, Sun Y, Sekiguchi K, Kondo S, Maekawa T, Takita M JMIR Public Health Surveill. 2024; 10:e57742.

PMID: 39037745 PMC: 11375397. DOI: 10.2196/57742.

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

Chaves J, da Silva M, Alencar R, Evsukoff A, Vieira V Data Brief. 2023; 51:109695.

PMID: 37965603 PMC: 10641473. DOI: 10.1016/j.dib.2023.109695.

Differences in the spatial landscape of urban mobility: Gender and socioeconomic perspectives.

Macedo M, Lotero L, Cardillo A, Menezes R, Barbosa H PLoS One. 2022; 17(3):e0260874.

PMID: 35235562 PMC: 8890667. DOI: 10.1371/journal.pone.0260874.

Uncovering structural diversity in commuting networks: global and local entropy.

Marin V, Molinero C, Arcaute E Sci Rep. 2022; 12(1):1684.

PMID: 35102190 PMC: 8803921. DOI: 10.1038/s41598-022-05556-6.

Information Theory for Human and Social Processes.

Hilbert M Entropy (Basel). 2020; 23(1).

PMID: 33374607 PMC: 7822471. DOI: 10.3390/e23010009.

References

Krieger N . Embodying inequality: a review of concepts, measures, and methods for studying health consequences of discrimination. Int J Health Serv. 1999; 29(2):295-352. DOI: 10.2190/M11W-VWXE-KQM9-G97Q. View

Blumenstock J, Cadamuro G, On R . Predicting poverty and wealth from mobile phone metadata. Science. 2015; 350(6264):1073-6. DOI: 10.1126/science.aac4420. View

Louf R, Barthelemy M . Patterns of Residential Segregation. PLoS One. 2016; 11(6):e0157476. PMC: 4912131. DOI: 10.1371/journal.pone.0157476. View

Lenormand M, Picornell M, Cantu-Ros O, Louail T, Herranz R, Barthelemy M . Comparing and modelling land use organization in cities. R Soc Open Sci. 2016; 2(12):150449. PMC: 4807451. DOI: 10.1098/rsos.150449. View

Lamanna F, Lenormand M, Salas-Olmedo M, Romanillos G, Goncalves B, Ramasco J . Immigrant community integration in world cities. PLoS One. 2018; 13(3):e0191612. PMC: 5851540. DOI: 10.1371/journal.pone.0191612. View

Song C, Qu Z, Blumm N, Barabasi A . Limits of predictability in human mobility. Science. 2010; 327(5968):1018-21. DOI: 10.1126/science.1177170. View

Batty M . Big data, smart cities and city planning. Dialogues Hum Geogr. 2018; 3(3):274-279. PMC: 5808818. DOI: 10.1177/2043820613513390. View

Lenormand M, Luque S, Langemeyer J, Tenerelli P, Zulian G, Aalders I . Multiscale socio-ecological networks in the age of information. PLoS One. 2018; 13(11):e0206672. PMC: 6211716. DOI: 10.1371/journal.pone.0206672. View

Phithakkitnukoon S, Smoreda Z, Olivier P . Socio-geography of human mobility: a study using longitudinal mobile phone data. PLoS One. 2012; 7(6):e39253. PMC: 3386290. DOI: 10.1371/journal.pone.0039253. View

10.

Eagle N, Macy M, Claxton R . Network diversity and economic development. Science. 2010; 328(5981):1029-31. DOI: 10.1126/science.1186605. View

11.

Lotero L, Hurtado R, Floria L, Gomez-Gardenes J . Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes. R Soc Open Sci. 2016; 3(10):150654. PMC: 5098956. DOI: 10.1098/rsos.150654. View

12.

Bettencourt L, Samaniego H, Youn H . Professional diversity and the productivity of cities. Sci Rep. 2014; 4:5393. PMC: 4066264. DOI: 10.1038/srep05393. View

13.

Louail T, Lenormand M, Cantu Ros O, Picornell M, Herranz R, Frias-Martinez E . From mobile phone data to the spatial structure of cities. Sci Rep. 2014; 4:5276. PMC: 4055889. DOI: 10.1038/srep05276. View

14.

Panigutti C, Tizzoni M, Bajardi P, Smoreda Z, Colizza V . Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models. R Soc Open Sci. 2017; 4(5):160950. PMC: 5451791. DOI: 10.1098/rsos.160950. View

15.

Onnela J, Saramaki J, Hyvonen J, Szabo G, Lazer D, Kaski K . Structure and tie strengths in mobile communication networks. Proc Natl Acad Sci U S A. 2007; 104(18):7332-6. PMC: 1863470. DOI: 10.1073/pnas.0610245104. View

16.

Gonzalez M, Hidalgo C, Barabasi A . Understanding individual human mobility patterns. Nature. 2008; 453(7196):779-82. DOI: 10.1038/nature06958. View

17.

Netto V, Brigatti E, Meirelles J, Ribeiro F, Pace B, Cacholas C . Cities, from Information to Interaction. Entropy (Basel). 2020; 20(11). PMC: 7512396. DOI: 10.3390/e20110834. View

18.

Dannemann T, Sotomayor-Gomez B, Samaniego H . The time geography of segregation during working hours. R Soc Open Sci. 2018; 5(10):180749. PMC: 6227938. DOI: 10.1098/rsos.180749. View

19.

Louail T, Lenormand M, Arias J, Ramasco J . Crowdsourcing the Robin Hood effect in cities. Appl Netw Sci. 2018; 2(1):11. PMC: 6214245. DOI: 10.1007/s41109-017-0026-3. View