Spatially explicit demographic projections for brazilian metropolitan areas by 2020 and 2030
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
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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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 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.publisher.initials.fl_str_mv |
UFMG |
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Brasil |
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FCE - DEPARTAMENTO DE DEMOGRAFIA IGC - DEPARTAMENTO DE GEOGRAFIA |
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Universidade Federal de Minas Gerais |
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