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Mapping Crime: Understanding Hot Spots

Much of crime mapping is devoted to detecting high-crime-density areas known as hot spots. Hot spot analysis helps police identify high-crime areas, types of crime being committed, and the best way to respond. This report discusses hot spot analysis techniques and software and identifies when to use each one.

Title:  Mapping Crime: Understanding Hot Spots
Author: Alberto R. Gonzales, Regina B. Schofield & Sarah V. Hart
Date published: August 2005
Number of pages: 79
Availability: Download full report PDF 251Kb

Crime is not spread evenly across maps. It clumps in some areas and is absent in others. People use this knowledge in their daily activities. They avoid some places and seek out others. Their choices of neighbourhoods, schools, shops, streets, and recreation are governed partially by the understanding that their chances of being a victim are greater in some of these places than in others.

Different kinds of hot spots, which develop from different causes, require different kinds of police action. For crime mappers, this means that the visual display of the crime pattern on the map should be consistent with the type of hot spot and possible police action. The visual display of a crime pattern on a map should be consistent with the type of hot spot and possible police action. For example, when hot spots are at specific addresses, a dot map is more appropriate than an area map, which would be too imprecise.

Preliminary global statistics have shown how simple-to-apply tests can reveal an understanding of what is to be expected in a hot spot map, even before the map has been created. Tests for clustering are particularly important. Analysts may waste valuable resource time in their attempts to create a crime hot spot map if a test such as the NNI quickly reveals that no clusters, and thus no hot spots, exist in their data. The different mapping techniques have revealed the different applications to which they are suited and demonstrated the advantages and disadvantages in their underlying routines and the mapping outputs they generate. The kernel density estimation method in particular has been demonstrated as being more than just a method that presents an attractive map of crime, but is a robust technique suited to understanding spatial patterns of crime hot spots.

Also important to remember is that map production is an iterative process. The first map produced is very rarely the one presented to the target audience. The intended message should be seen as the driving force behind what the map should look like. Map creation and design requires flexibility. Methods and techniques described in this report  retain this flexibility but suggest some simple-to-apply operations that help to understand crime hot spots.

Key Findings

• Identifying hot spots requires multiple techniques; no single method is sufficient to analyze all types of crime.
   

• Current mapping technologies have significantly improved the ability of crime analysts and researchers to understand crime patterns and victimization.
   

• Crime hot spot maps can most effectively guide police action when production of the maps is guided by crime theories (place, victim, street, or neighborhood).