CrimAnalyzer: Understanding Crime Patterns in Sao Paulo

Autor(es)

Garcia, Germain ^[1] ; Silveira, Jaqueline ^[1] ; Poco, Jorge ^{[2, 3]} ; Paiva, Afonso ^[1] ; Nery, Marcelo Batista ^{[4, 5]} ; Silva, Claudio T. ^[6] ; Adorno, Sergio ^[7] ; Nonato, Luis Gustavo ^{[1, 8]}

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Ciencias Matemat & Comp, BR-13566590 Sao Carlos - Brazil

^[2] Fundacao Getulio Vargas, Sch Appl Math, Sao Paulo, SP - Brazil

^[3] Univ Catolica San Pablo, Arequipa 04001 - Peru

^[4] RIDC FAPESP, Ctr Study Violence, Sao Paulo, SP - Brazil

^[5] Inst Adv Studies, Global Cities Program, Sao Paulo, SP - Brazil

^[6] NYU, Comp Sci & Engn & Data Sci, New York, NY 10003 - USA

^[7] Univ Sao Paulo, Nucleo Estudos Violencia, BR-05508900 Sao Paulo - Brazil

^[8] NYU, Ctr Data Sci, New York, NY 10003 - USA

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS; v. 27, n. 4, p. 2313-2328, APR 1 2021.
• Citações Web of Science: 0

Resumo

Sao Paulo is the largest city in South America, with crime rates that reflect its size. The number and type of crimes vary considerably around the city, assuming different patterns depending on urban and social characteristics of each particular location. Previous works have mostly focused on the analysis of crimes with the intent of uncovering patterns associated to social factors, seasonality, and urban routine activities. Therefore, those studies and tools are more global in the sense that they are not designed to investigate specific regions of the city such as particular neighborhoods, avenues, or public areas. Tools able to explore specific locations of the city are essential for domain experts to accomplish their analysis in a bottom-up fashion, revealing how urban features related to mobility, passersby behavior, and presence of public infrastructures (e.g., terminals of public transportation and schools) can influence the quantity and type of crimes. In this paper, we present CrimAnalyzer, a visual analytic tool that allows users to study the behavior of crimes in specific regions of a city. The system allows users to identify local hotspots and the pattern of crimes associated to them, while still showing how hotspots and corresponding crime patterns change over time. CrimAnalyzer has been developed from the needs of a team of experts in criminology and deals with three major challenges: i) flexibility to explore local regions and understand their crime patterns, ii) identification of spatial crime hotspots that might not be the most prevalent ones in terms of the number of crimes but that are important enough to be investigated, and iii) understand the dynamic of crime patterns over time. The effectiveness and usefulness of the proposed system are demonstrated by qualitative and quantitative comparisons as well as by case studies run by domain experts involving real data. The experiments show the capability of CrimAnalyzer in identifying crime-related phenomena. (AU)

• Processo FAPESP: 16/04391-2 - Operadores de morfologia matemática para a análise visual de dados urbanos
• Beneficiário: Fábio Augusto Salve Dias
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado
• Processo FAPESP: 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo?
• Beneficiário: Alexandre Xavier Falcão
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 17/05416-1 - Analise visual de métodos de aprendizado de máquina: um ensaio prático a partir de dados de crime da cidade de São Paulo.
• Beneficiário: Germain García Zanabria
• Modalidade de apoio: Bolsas no Brasil - Doutorado