Overview

This one-day short course will give you a comprehensive understanding of crime hotspots, covering analytical techniques and the theory that underpins them.

It's a GIS-based course aimed at introducing intelligence, crime and community safety analysts and researchers to techniques for identifying and understanding hotspots and other geographic patterns of crime.

Who this course is for

This GIS-based course is for users of MapInfo, ArcGIS (ArcMAP) and CadCorp SIS.

It's aimed at:

• police and CSP analysts
• researchers 
• information officers

It may also be useful if you're interested in GIS-based mapping, spatial statistics, thematic mapping, or kernel density estimation.

Course content

The course includes the following topics:

Theoretical principles for understanding hotspots

We'll define the term 'hotspot', explore the diagnostics of hotspots and discuss several key spatial theories that can be used to help explain why a hotspot may exist.

Nearest neighbour and standard distance statistics for describing crime patterns

These statistics can provide a useful insight into the types of geographic patterns that exist in crime data before the data is displayed on a map. For example, these tests can be used to explore if evidence of spatial clustering exists and how dispersed the distribution is relative to other crime types or crime periods.

Point maps

Point mapping is a common means of displaying crime events, but difficulties may arise in using this technique when handling large volumes of data or if locations of repeat events exist. We'll explore the practical uses of this technique.

Geographic boundary thematic mapping

Thematic mapping of crime data, aggregated to geographical administrative boundary areas such as census output areas, wards, or police beats, is a popular method for visually crime patterns.

However, problems exist with this technique that can cause misleading interpretations of where crime may be most prevalent. This can be due to freedom of choice in the different thematic range settings that are possible for displaying comparative levels of crime, and from the problems associated with a concept called the 'modifiable area unit problem'. We'll demonstrate how the technique can be used, and discuss its practical application.

Quadrat thematic mapping

Quadrat thematic mapping is a technique that uses uniform grid cells (quadrats) of a specified user width to thematically shade crime patterns. We'll explore the advantages and disadvantages of this technique for helping to determine and understand crime hotspots.

Kernel density estimation (KDE)

KDE is a method that aggregates points within a specified search radius, and creates a smooth continuous surface that represents the density of events distributed across the area. We'll go through tools that can be used to generate KDE hotspot maps and discusses the technique's application. This includes discussion on the parameter settings that are required for KDE.

Entry requirements

You'll need at least a foundation in MapInfo, ArcGIS or Cadcorp SIS software.

The course is only suitable for users of Mapinfo, ArcView, ArcGIS, or Cadcorp SIS.

Cost and concessions

There's a 10% reduction for bookings of two or more people - all group delegates must be booked at the same time.

Course team

Spencer Chainey

Spencer is the Principal Research Associate at the UCL Department of Security and Crime Science. His particular research interests are in developing geographical crime analysis and crime mapping. He carries out most of his day-to-day work on developing the use of data, information sharing and analysis to aid intelligence development and decision-making by police forces, community safety partnerships, and national crime reduction and policing agencies.

Spencer's work has influenced national (UK) policy, and has contributed to policing and crime reduction developments in the USA, Canada, Brazil, China, Germany, Northern Ireland, Australia, New Zealand and South Africa. His work is also used in examples of good practice by the UK Cabinet Office (Social Exclusion Unit), Local Government Improvement and Development, The Home Office, the Audit Commission, The Housing Corporation and the United States National Institute of Justice.

Course information last modified: 30 Nov 2022, 16:00