Geo: A Visual Analytics Tool for Spatiotemporal Analysis

• José F. de Queiroz Neto Universidade Federal do Ceará (UFC) / Igeos AI Company
• José Antônio F. de Macêdo Universidade Federal do Ceará (UFC)
• Erick L. Trentini Universidade Federal do Ceará (UFC) / Igeos AI Company
• Samir B. Chaves Universidade Federal do Ceará (UFC) / Igeos AI Company https://orcid.org/0009-0007-7006-5837
• João Araújo Castelo Branco Universidade Federal do Ceará (UFC) / Igeos AI Company

DOI: https://doi.org/10.5753/sbbd_estendido.2025.247827

Resumo

This paper presents Geo, a spatiotemporal analysis tool designed to support criminal analysis tasks such as hotspot detection and police patrol route planning. The system addresses the gap between traditional hotspot mapping and actionable patrol deployment by combining three techniques: MSKDE for high-resolution density estimation, SHOC for intuitive temporal comparison of crime hotspots, and HotSee for generating patrol routes along high-risk street segments. Through a real case study on robbery incidents in Vila Sônia, São Paulo, the paper demonstrates how Geo enables analysts to identify spatial and temporal crime patterns, adapt analysis to street networks, and create operational patrol routes. The results highlight Geo’s effectiveness in bridging strategic crime mapping and tactical decision-making, with future work aimed at real-time data integration and broader applications in public safety.

Palavras-chave: Spatiotemporal Analysis, Crime Mapping, Hotspot Detection, Patrol Route Planning, Public Safety

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Nunes Junior, F. C. F., Matias, J. A. S., Chainey, S. P., Coelho da Silva, T. L., de Macedo, J. A. F., Magalhães, R. P., de Queiroz Neto, J. F., and Porcino, W. C. (2025). Route Generation Heuristics for the Automated Creation of Hot Spots Policing Patrol Routes, pages 115–135. Springer Nature Switzerland, Cham.