GIS for crime analysis

Detalhes bibliográficos
Autor(a) principal: Ferreira, Jorge
Data de Publicação: 2012
Outros Autores: João, Paulo, Martins, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/158324
Resumo: The term crime analysis refers to a concept and to a discipline practiced in the policing community. It includes analysis of more than just a crime, which is why some authors refer to it as public safety analysis. However, over the last few years crime an alysis has become a general term that includes a lot of research subcategories: intelligence analysis, criminal investigative analysis, tactical crime analysis, strategic crime analysis, operation analysis and administrative crime analysis. Crime mapping and spatial analysis complements all of them and plays a crucial role in defining new forms of representation and visualization to better understand crime and to respond adequately to the problem of criminality. A new worldwide socio‑economical order lead to an increasing number on crime rates and raised the need to find new ways to handle information about criminality. To better understand its causes, local, regional and national security authorities turned to new decision support tools such as Geographi c Information Systems (GIS) and other information technologies to find better solutions. To understand the magnitude of all the variables involved it is necessary to spatially capture and correlate them. Only by doing that it´s possible to quantify and qualify some hidden aspects of the phenomena. The city of Lisbon with is new proposed administrative division, reducing from 53 to 24 freguesias (minimum administrative division and similar to parishs) implies an enormous degree of uncertainty in the observation and location of criminal data. As the crime is not treated with an exact point, but at the level of parish, it implies that larger parishes are treated by the average crime regardless of place of occurrence. This research combines statistica l methods (cluster analysis) and spatial models created with GIS, based on police crime reports. It also details a framework for short‑term tactical deployment of police resources in which the objective is the identification of areas where the crime lev els are high (enough) to enable accurate predictive models as well as to produce rigorous thematic maps. In recent years police services have engaged on proactive and Intelligence‑Led Policing (ILP) methods. This advance was coincident with the recogn ition of law‑enforcement solutions at local level. This paper also engages an approach to ILP as a methodology to provide the necessary tools for Decision Support System (DSS) of police departments.
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spelling GIS for crime analysisGeography for predictive modelsSDG 16 - Peace, Justice and Strong InstitutionsThe term crime analysis refers to a concept and to a discipline practiced in the policing community. It includes analysis of more than just a crime, which is why some authors refer to it as public safety analysis. However, over the last few years crime an alysis has become a general term that includes a lot of research subcategories: intelligence analysis, criminal investigative analysis, tactical crime analysis, strategic crime analysis, operation analysis and administrative crime analysis. Crime mapping and spatial analysis complements all of them and plays a crucial role in defining new forms of representation and visualization to better understand crime and to respond adequately to the problem of criminality. A new worldwide socio‑economical order lead to an increasing number on crime rates and raised the need to find new ways to handle information about criminality. To better understand its causes, local, regional and national security authorities turned to new decision support tools such as Geographi c Information Systems (GIS) and other information technologies to find better solutions. To understand the magnitude of all the variables involved it is necessary to spatially capture and correlate them. Only by doing that it´s possible to quantify and qualify some hidden aspects of the phenomena. The city of Lisbon with is new proposed administrative division, reducing from 53 to 24 freguesias (minimum administrative division and similar to parishs) implies an enormous degree of uncertainty in the observation and location of criminal data. As the crime is not treated with an exact point, but at the level of parish, it implies that larger parishes are treated by the average crime regardless of place of occurrence. This research combines statistica l methods (cluster analysis) and spatial models created with GIS, based on police crime reports. It also details a framework for short‑term tactical deployment of police resources in which the objective is the identification of areas where the crime lev els are high (enough) to enable accurate predictive models as well as to produce rigorous thematic maps. In recent years police services have engaged on proactive and Intelligence‑Led Policing (ILP) methods. This advance was coincident with the recogn ition of law‑enforcement solutions at local level. This paper also engages an approach to ILP as a methodology to provide the necessary tools for Decision Support System (DSS) of police departments.Departamento de Geografia e Planeamento Regional (DGPR)e-GEO -Centro de Estudos de Geografia e Planeamento RegionalRUNFerreira, JorgeJoão, PauloMartins, José2023-09-26T22:20:43Z20122012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article13application/pdfhttp://hdl.handle.net/10362/158324eng1566-6379PURE: 72378018info: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:RCAAP2024-05-22T18:14:39Zoai:run.unl.pt:10362/158324Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:14:39Repositório 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 GIS for crime analysis
Geography for predictive models
title GIS for crime analysis
spellingShingle GIS for crime analysis
Ferreira, Jorge
SDG 16 - Peace, Justice and Strong Institutions
title_short GIS for crime analysis
title_full GIS for crime analysis
title_fullStr GIS for crime analysis
title_full_unstemmed GIS for crime analysis
title_sort GIS for crime analysis
author Ferreira, Jorge
author_facet Ferreira, Jorge
João, Paulo
Martins, José
author_role author
author2 João, Paulo
Martins, José
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Geografia e Planeamento Regional (DGPR)
e-GEO -Centro de Estudos de Geografia e Planeamento Regional
RUN
dc.contributor.author.fl_str_mv Ferreira, Jorge
João, Paulo
Martins, José
dc.subject.por.fl_str_mv SDG 16 - Peace, Justice and Strong Institutions
topic SDG 16 - Peace, Justice and Strong Institutions
description The term crime analysis refers to a concept and to a discipline practiced in the policing community. It includes analysis of more than just a crime, which is why some authors refer to it as public safety analysis. However, over the last few years crime an alysis has become a general term that includes a lot of research subcategories: intelligence analysis, criminal investigative analysis, tactical crime analysis, strategic crime analysis, operation analysis and administrative crime analysis. Crime mapping and spatial analysis complements all of them and plays a crucial role in defining new forms of representation and visualization to better understand crime and to respond adequately to the problem of criminality. A new worldwide socio‑economical order lead to an increasing number on crime rates and raised the need to find new ways to handle information about criminality. To better understand its causes, local, regional and national security authorities turned to new decision support tools such as Geographi c Information Systems (GIS) and other information technologies to find better solutions. To understand the magnitude of all the variables involved it is necessary to spatially capture and correlate them. Only by doing that it´s possible to quantify and qualify some hidden aspects of the phenomena. The city of Lisbon with is new proposed administrative division, reducing from 53 to 24 freguesias (minimum administrative division and similar to parishs) implies an enormous degree of uncertainty in the observation and location of criminal data. As the crime is not treated with an exact point, but at the level of parish, it implies that larger parishes are treated by the average crime regardless of place of occurrence. This research combines statistica l methods (cluster analysis) and spatial models created with GIS, based on police crime reports. It also details a framework for short‑term tactical deployment of police resources in which the objective is the identification of areas where the crime lev els are high (enough) to enable accurate predictive models as well as to produce rigorous thematic maps. In recent years police services have engaged on proactive and Intelligence‑Led Policing (ILP) methods. This advance was coincident with the recogn ition of law‑enforcement solutions at local level. This paper also engages an approach to ILP as a methodology to provide the necessary tools for Decision Support System (DSS) of police departments.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01T00:00:00Z
2023-09-26T22:20:43Z
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dc.relation.none.fl_str_mv 1566-6379
PURE: 72378018
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