Mapping the Future: Using Spatial Similarity Search for Urban Crime Analysis
Mapping the Future: Using Spatial Similarity Search for Urban Crime Analysis
Abstract
Keeping communities safe is a major priority for modern cities, and leaders are constantly looking for smarter ways to stay ahead of crime. This presentation explores how GIS technology can use similarity searches to help forecast future high-risk areas, using Chicago as a primary case study. By looking at how different neighborhoods share similar population traits, economic conditions, and past crime trends, analysts can better understand the underlying factors driving crime. The session discusses how comparing these neighborhood profiles gives city planners and law enforcement a clearer picture of emerging risks. Ultimately, it highlights how blending spatial mapping with pattern analysis helps communities move from reacting to crime to stopping it before it starts.