More CCA Awards & Scholarships
CCA President’s Prize 2023 Winner (University Level) – “Hotspot Policing for the City of Toronto“
The 2023 University level award was presented to Sigao Li from Toronto Metropolitan University for his map titled “Hotspot Policing for the City of Toronto”
Design Objectives:
This map poster focuses on how the hotspot map can help to reduce police response time, improve the efficiency of police patrols by detecting high-crime areas, and provide potential transportation infrastructure or regulation improvements by locating high-incident-prone areas.
Cartographic Design: The poster will include a workflow for the methodology of this study, one hotspot major crime map, one hotspot traffic collision map, and one hotspot policing map created by combining the two datasets.
Implementation: The main component of the poster is a 250m by 250m rectangular grid covering the city of Toronto. The point data of Major Crime and Traffic Collision are assigned to these grids, then normalized using the method of Z-Score. Finally, the results are visualized on the maps. Road networks, cycling routes, traffic cameras, police facilities, patrol zones, and social deprivation index will be assigned to the appropriate map.
Possible Uses: The application of hot spot policing in urban areas has a significant effect on reducing the crime rate, and the police dispatching due to preventive patrols in hot crime areas will not significantly divert the crime space (Weisburd et al., 2017; Telep & Hibdon, 2018). In terms of traffic, installing traffic cameras in high-accident areas can significantly reduce traffic collisions, and the response time of police to traffic collisions is positively correlated with the survival of the accident party (Martinez-Ruiz et al., 2019; Liu, 2022).
Limitations: The Major Crime and Traffic Collisions data are selected from 2017 to 2022. While presenting 5-year overall crime/collision hotspots can provide Toronto police concerning priority patrols, data changes every year. Future research could create a yearly heat map and compare the hotspots, and perhaps it could detect areas with increased rates.
