Advanced Hotspot Analysis: Crime, Intelligence and Community Safety
Course
In London
Description
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Type
Course
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Level
Advanced
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Location
London
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Class hours
7h
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Start date
Different dates available
This one-day hands on GIS-based training course develops the existing skills that an experienced intelligence/crime/community safety analyst has for understanding hotspots.
It does this by introducing you to several advanced techniques that can help you explore spatial patterns in crime data.
In particular, the course aims to develop your skills in spatial statistical techniques that provide a means of testing for significance (i.e. testing and observing in statistical terms whether a geographic pattern is particularly unusual).
The course may introduce new techniques and demystify others, with the aim of exploring their practical application for understanding hotspots.
The course is run by UCL's Jill Dando Institute of Security and Crime Science. It's held at our offices in London, but can also be delivered at your site for a minimum of six staff.
Facilities
Location
Start date
Start date
About this course
This GIS-based course is for users of MapInfo, ArcGIS (ArcMAP) and CadCorp SIS.
This course is suitable for:
police
community safety partnership (CSP) analysts
researchers
information officers
To take this course you'll need:
at least a foundation in MapInfo, ArcGIS or Cadcorp SIS software
to be experienced in using KDE
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Subjects
- Testing
- GIS
- Police
- CSP
- Researchers
- Information officers
- Clustering techniques
- Hotspots
- Advanced Hotspot Analysis
- Crime
- Community Safety
Course programme
The methods and techniques you'll learn about on the course include the following:
Risk-based clustering techniquesTechniques such as dual kernel density estimation allow for a secondary variable (e.g. population) to be considered in determining hotspots. That is, these techniques can be used to identify hotspots based on not only the distribution of crime, but how the underlying population influences this spatial distribution. We examine the use of dual KDE and its practical application.
Identifying emerging problem areasA common analytical requirement is to determine how patterns of crime have changed over time. One approach for observing changes in crime is with map subtraction, where hotspot maps are created for two time periods, and a change map is produced showing those areas where crime has reduced or has increased. A problem with the map subtraction approach is that the change map can result in identifying a large number of areas where crime has increased, restricting the ability to be selective in the targeting of resources. On this course we introduce a more useful analytical approach which involves identifying areas that have contributed most to an increase. By doing this we can help to target response resources more specifically.
Local indicators of spatial association: local Moran’s I, local Geary’s C, and the Getis- and Ord-Gi and Gi* statisticsThis group of spatial statistics provides a means of extending beyond methods such as kernel density estimation by identifying those areas where the clustering of crime points is significant. That is, they can determine areas that can be statistically defined as hot from those that are not, plus rank each hotspot according to significance thresholds (i.e. 95%, 99%, 99.9%). This part of the course guides you through these techniques and discusses their practical application. Particular emphasis is placed on using the Gi* statistic.
Software usedSome of the functionality we teach on the course is unavailable in standard GIS packages. ArcGIS v9.3 and above has the functionality for most of what we teach on this course, whereas MapInfo is still rather limited. We therefore make use of freeware software that includes the Dispersion Calculator, CrimeStat and RooksCase to perform some of the analytical techniques.
Advanced Hotspot Analysis: Crime, Intelligence and Community Safety