Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/126934 |
Resumo: | Tavares, J. P., & Costa, A. C. (2021). Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal. ISPRS International Journal of Geo-Information, 10(11), 1-18. [731]. https://doi.org/10.3390/ijgi10110731 |
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Spatial Modeling and Analysis of the Determinants of Property Crime in PortugalCrime concentration and hot spot analysisSpatial regression analysisGeographic crime analysisGeographically Weighted Poisson RegressionSpatial heterogeneityPortugalGeography, Planning and DevelopmentComputers in Earth SciencesEarth and Planetary Sciences (miscellaneous)SDG 16 - Peace, Justice and Strong InstitutionsSDG 4 - Quality EducationSDG 8 - Decent Work and Economic GrowthTavares, J. P., & Costa, A. C. (2021). Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal. ISPRS International Journal of Geo-Information, 10(11), 1-18. [731]. https://doi.org/10.3390/ijgi10110731Many researchers have unraveled innovative ways of examining geographic information to better understand the determinants of crime, thus contributing to an improved understanding of the phenomenon. Property crimes represent more than half of the crimes reported in Portugal. This study investigates the spatial distribution of crimes against property in mainland Portugal with the primary goal of determining which demographic and socioeconomic factors may be associated with crime incidence in each municipality. For this purpose, Geographic Information System (GIS) tools were used to analyze spatial patterns, and different Poisson-based regression models were investigated, namely global models, local Geographically Weighted Poisson Regression (GWPR) models, and semi-parametric GWPR models. The GWPR model with eight independent variables outperformed the others. Its independent variables were the young resident population, retention and dropout rates in basic education, gross enrollment rate, conventional dwellings, Guaranteed Minimum Income and Social Integration Benefit, purchasing power per capita, unemployment rate, and foreign population. The model presents a better fit in the metropolitan areas of Lisbon and Porto and their neighboring municipalities. The association of each independent variable with crime varies significantly across municipalities. Consequently, these particularities should be considered in the design of policies to reduce the rate of property crimes.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNTavares, Joana PauloCosta, Ana Cristina2021-10-31T04:02:08Z2021-11-012021-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article18application/pdfhttp://hdl.handle.net/10362/126934eng2220-9964PURE: 34551508https://doi.org/10.3390/ijgi10110731info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:07:06Zoai:run.unl.pt:10362/126934Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:46:00.411861Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
title |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
spellingShingle |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal Tavares, Joana Paulo Crime concentration and hot spot analysis Spatial regression analysis Geographic crime analysis Geographically Weighted Poisson Regression Spatial heterogeneity Portugal Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 16 - Peace, Justice and Strong Institutions SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth |
title_short |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
title_full |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
title_fullStr |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
title_full_unstemmed |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
title_sort |
Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal |
author |
Tavares, Joana Paulo |
author_facet |
Tavares, Joana Paulo Costa, Ana Cristina |
author_role |
author |
author2 |
Costa, Ana Cristina |
author2_role |
author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) Information Management Research Center (MagIC) - NOVA Information Management School RUN |
dc.contributor.author.fl_str_mv |
Tavares, Joana Paulo Costa, Ana Cristina |
dc.subject.por.fl_str_mv |
Crime concentration and hot spot analysis Spatial regression analysis Geographic crime analysis Geographically Weighted Poisson Regression Spatial heterogeneity Portugal Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 16 - Peace, Justice and Strong Institutions SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth |
topic |
Crime concentration and hot spot analysis Spatial regression analysis Geographic crime analysis Geographically Weighted Poisson Regression Spatial heterogeneity Portugal Geography, Planning and Development Computers in Earth Sciences Earth and Planetary Sciences (miscellaneous) SDG 16 - Peace, Justice and Strong Institutions SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth |
description |
Tavares, J. P., & Costa, A. C. (2021). Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal. ISPRS International Journal of Geo-Information, 10(11), 1-18. [731]. https://doi.org/10.3390/ijgi10110731 |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-31T04:02:08Z 2021-11-01 2021-11-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/126934 |
url |
http://hdl.handle.net/10362/126934 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2220-9964 PURE: 34551508 https://doi.org/10.3390/ijgi10110731 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
18 application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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