Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal

Detalhes bibliográficos
Autor(a) principal: Tavares, Joana Paulo
Data de Publicação: 2021
Outros Autores: Costa, Ana Cristina
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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spelling 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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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