Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030

Detalhes bibliográficos
Autor(a) principal: Glauco Umbelino
Data de Publicação: 2017
Outros Autores: Diego Rodrigues Macedo, Alisson Barbieri, Gilvan Ramalho Guedes, Alfredo Costa, United Nations, Ministério do Meio Ambiente
Tipo de documento: Artigo de conferência
Idioma: por
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://hdl.handle.net/1843/54028
https://orcid.org/0000-0002-1178-4969
https://orcid.org/0000-0002-1133-1089
https://orcid.org/0000-0001-8231-238X
https://orcid.org/0000-0002-1735-6711
Resumo: Simulation models coupled with Geographic Information Systems are now applied to several areas and have great potential for demographic studies. Demographic projections can tell us “how much we will be”, but when coupled with GIS tools these projections can add the ability to show “where we will be”. This paper simulates the growth of urban areas, the resident population, and their households for the Brazilian Metropolitan Regions of São Paulo, Rio de Janeiro, Belo Horizonte, Brasilia, and Belém for 2020 and 2030. Based on demographic data measured between 2000 and 2010, and the mapping of urban areas through satellite images between 2000 and 2016, we used cellular automata models coupled with GIS to simulate future scenarios of population and urban growth. Our results suggest a decrease in the growth rate of urban areas despite the population and household growth in the coming decades. These trends are indicative of increasing intra-urban density, possibly reflected in the increase in building verticalization. Population is projected to grow at a slower pace than households, reflecting a decrease in the number of inhabitants per household in the study areas.
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spelling 2023-05-26T20:17:33Z2023-05-26T20:17:33Z2017XXVIII International Population Conference15http://hdl.handle.net/1843/54028https://orcid.org/0000-0002-1178-4969https://orcid.org/0000-0002-1178-4969https://orcid.org/0000-0002-1133-1089https://orcid.org/0000-0001-8231-238Xhttps://orcid.org/0000-0002-1735-6711Simulation models coupled with Geographic Information Systems are now applied to several areas and have great potential for demographic studies. Demographic projections can tell us “how much we will be”, but when coupled with GIS tools these projections can add the ability to show “where we will be”. This paper simulates the growth of urban areas, the resident population, and their households for the Brazilian Metropolitan Regions of São Paulo, Rio de Janeiro, Belo Horizonte, Brasilia, and Belém for 2020 and 2030. Based on demographic data measured between 2000 and 2010, and the mapping of urban areas through satellite images between 2000 and 2016, we used cellular automata models coupled with GIS to simulate future scenarios of population and urban growth. Our results suggest a decrease in the growth rate of urban areas despite the population and household growth in the coming decades. These trends are indicative of increasing intra-urban density, possibly reflected in the increase in building verticalization. Population is projected to grow at a slower pace than households, reflecting a decrease in the number of inhabitants per household in the study areas.porUniversidade Federal de Minas GeraisUFMGBrasilFCE - DEPARTAMENTO DE DEMOGRAFIAIGC - DEPARTAMENTO DE GEOGRAFIAInternational Population ConferenceGeografiaGeociênciasUrban sprawlGeotechnologyCellular automataSimulation modelsMetropolitan areas in BrazilSpatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttps://zenodo.org/record/2576592Glauco UmbelinoDiego Rodrigues MacedoAlisson BarbieriGilvan Ramalho GuedesAlfredo CostaUnited NationsMinistério do Meio Ambienteinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/54028/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALSpatially Explicit Demographic Projections for Brazilian Metropolitan Areas by 2020 and 2030.pdfSpatially Explicit Demographic Projections for Brazilian Metropolitan Areas by 2020 and 2030.pdfapplication/pdf205868https://repositorio.ufmg.br/bitstream/1843/54028/2/Spatially%20Explicit%20Demographic%20Projections%20for%20Brazilian%20Metropolitan%20Areas%20by%202020%20and%202030.pdfeea2af2f4c33e4984ae2ed0bd1baa606MD521843/540282023-05-26 17:17:33.266oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-05-26T20:17:33Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
title Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
spellingShingle Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
Glauco Umbelino
Urban sprawl
Geotechnology
Cellular automata
Simulation models
Metropolitan areas in Brazil
Geografia
Geociências
title_short Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
title_full Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
title_fullStr Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
title_full_unstemmed Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
title_sort Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
author Glauco Umbelino
author_facet Glauco Umbelino
Diego Rodrigues Macedo
Alisson Barbieri
Gilvan Ramalho Guedes
Alfredo Costa
United Nations
Ministério do Meio Ambiente
author_role author
author2 Diego Rodrigues Macedo
Alisson Barbieri
Gilvan Ramalho Guedes
Alfredo Costa
United Nations
Ministério do Meio Ambiente
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Glauco Umbelino
Diego Rodrigues Macedo
Alisson Barbieri
Gilvan Ramalho Guedes
Alfredo Costa
United Nations
Ministério do Meio Ambiente
dc.subject.por.fl_str_mv Urban sprawl
Geotechnology
Cellular automata
Simulation models
Metropolitan areas in Brazil
topic Urban sprawl
Geotechnology
Cellular automata
Simulation models
Metropolitan areas in Brazil
Geografia
Geociências
dc.subject.other.pt_BR.fl_str_mv Geografia
Geociências
description Simulation models coupled with Geographic Information Systems are now applied to several areas and have great potential for demographic studies. Demographic projections can tell us “how much we will be”, but when coupled with GIS tools these projections can add the ability to show “where we will be”. This paper simulates the growth of urban areas, the resident population, and their households for the Brazilian Metropolitan Regions of São Paulo, Rio de Janeiro, Belo Horizonte, Brasilia, and Belém for 2020 and 2030. Based on demographic data measured between 2000 and 2010, and the mapping of urban areas through satellite images between 2000 and 2016, we used cellular automata models coupled with GIS to simulate future scenarios of population and urban growth. Our results suggest a decrease in the growth rate of urban areas despite the population and household growth in the coming decades. These trends are indicative of increasing intra-urban density, possibly reflected in the increase in building verticalization. Population is projected to grow at a slower pace than households, reflecting a decrease in the number of inhabitants per household in the study areas.
publishDate 2017
dc.date.issued.fl_str_mv 2017
dc.date.accessioned.fl_str_mv 2023-05-26T20:17:33Z
dc.date.available.fl_str_mv 2023-05-26T20:17:33Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/54028
dc.identifier.orcid.pt_BR.fl_str_mv https://orcid.org/0000-0002-1178-4969
https://orcid.org/0000-0002-1178-4969
https://orcid.org/0000-0002-1133-1089
https://orcid.org/0000-0001-8231-238X
https://orcid.org/0000-0002-1735-6711
url http://hdl.handle.net/1843/54028
https://orcid.org/0000-0002-1178-4969
https://orcid.org/0000-0002-1133-1089
https://orcid.org/0000-0001-8231-238X
https://orcid.org/0000-0002-1735-6711
dc.language.iso.fl_str_mv por
language por
dc.relation.ispartof.pt_BR.fl_str_mv International Population Conference
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.publisher.initials.fl_str_mv UFMG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv FCE - DEPARTAMENTO DE DEMOGRAFIA
IGC - DEPARTAMENTO DE GEOGRAFIA
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
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