| Full text | |
| Author(s): |
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]
Total Authors: 8
|
| Affiliation: | [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
Total Affiliations: 8
|
| Document type: | Journal article |
| Source: | IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS; v. 27, n. 4, p. 2313-2328, APR 1 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
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) | |
| FAPESP's process: | 16/04391-2 - Mathematical morphology operators for the visual analytics of urban data |
| Grantee: | Fábio Augusto Salve Dias |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/05416-1 - Visual Analytics of Machine Learning Methods: a practical essay from crime data in São Paulo |
| Grantee: | Germain García Zanabria |
| Support Opportunities: | Scholarships in Brazil - Doctorate |