Predictive Mapping (1 day course) (for users of ArcGIS, MapInfo or Cadcorp Map Modeller)
This 1-day GIS-based course explores the use of theoretically robust techniques for predicting where and when crime is likely to occur in the future. It draws heavily from our successful predictive policing and prospective mapping work that has been implemented in Greater Manchester, West Midlands and Derbyshire. The predictive mapping work we have initiated has been applied to many different types of crime, and not just burglary. This includes bike theft, violent crime, gun shootings and improvised explosive devices.
The course focuses on exploiting analytical methods for repeat victimisation, near repeat victimisation and hotspot analysis. We begin by critiquing approaches for predicting where and when crime is likely to occur in the future. We then focus on the technical process for identifying repeat victimisation (RV), and the metrics used for measuring these repeats. This helps to establish the extent of RV and the impact that any initiative may have in addressing RVs. We then explore the theory that underpins RV (boost and flag accounts), and extend this by considering the optimal foraging behaviour of offenders. This leads us towards evidencing patterns of near repeat victimisation (NRV), and how NRV can be measured and used in a predictive policing strategy.
We then explore mapping applications that can be used for predicting where crime is likely to happen in the future. This includes a critique of hotspot analysis, prospective mapping tools, and buffering areas of risk around recent incidents.
We also discuss the response opportunities that follow predictive mapping analysis, including tactical options for reducing future victimisation, offender detection opportunities, public reassurance and strategic resource targeting.
The course assumes each delegate is proficient in the use of their GIS, and is able to make use of the free Near Repeat Calculator tool.
Predictive Mapping (1 day course) (for users of ArcGIS, MapInfo and Cadcorp Map Modeller)
Aimed at: Police, CSP analysts, researchers and information officers
Length: 1 day
Entry requirements: The course is designed to cater for those that are proficient in the use of their GIS.
A. Predictive mapping techniques: a short critique
In the first session we critique many of the existing approaches for predictive mapping. We show evidence of what works ... and what doesn't. We provide the empirical grounding towards why repeat victimisation and near repeat victimisation analysis offers a useful means for crime prediction. We also explore the use of standard hotspot mapping for predicting crime.
B. Repeat victimisation: theoretical principles
This session explores the theoretical principles that help explain the reasons for repeat victimisation. We explore the concepts of the boost and flag accounts, and evidence from offender interviews. We also explore the concept of the offender as an optimal forager.
C. Measuring repeat victimisation
There are many metrics that can be used for measuring repeat victimisation. We explore the most useful metrics to use, and the technical challenges in measuring repeats. We use standard GIS tools for making these measurements, but also explore the use of add-on tools (e.g. ESRI Crime Analyst and MapInfo Hotspot Detective) where these are familiar and are available to delegates attending the course.
D. Near repeat victimisation: theoretical principles
This sessions extends the theoretical principles that explain repeats by considering how these also explain near repeat victimisation. We support this by evidencing findings from offender interviews and empirical studies of the near repeat patterns found in a wide range of crime and other incident types.
E. Measuring near repeats
In this session we make use of the Near Repeat Calculator for measuring patterns of NRVs. The Near Repeat Calculator is a free tool that runs as a executable file. We help delegates interpret the results and how they can be applied to the design of operational and strategic tactics for crime reduction. We also explore how the results of a NRV analysis can be mapped, showing how near repeats relate to their 'originator' offences.
F. Mapping where crime is likely to occur in the future
There are a number of mapping techniques that are used for identifying where crime is likely to occur in the future following an analysis that has evidenced patterns of repeat and near repeat victimisation. In this session we explore the use of cocooning mapping methods, identifying risk and hyper-risk areas (as buffers around recent incidents) and prospective mapping tools. We also explore the applicability of these tools against standard hotspot mapping methods for predicting crime in the near future, and where crime is likely to persist for longer periods.
F. Tactical, detection, and strategic response opportunities
In the last session we explore the tactical, investigative and strategic response opportunities that can assist in crime reduction and improving detection of offenders. We also explore how certain tactics can have a positive or negative impact on public reassurance.
Course tutor: Spencer Chainey
Predictive Mapping (1 day course)
Course Dates: To be confirmed. Please contact Peter Gudge via firstname.lastname@example.org if you would like to be notified when this is confirmed.
Course Cost: £475
Group Discount: 10% discount for bookings of two or more. To qualify, all group delegates must be booked at the same time.
Accommodation: UCL has a number of residences that are available to book when courses are held in the summer months. These are available from £45 per night. We recommend Frances Gardner House or James Lighthill House due to their proximity to the JDI and their facilities. Please visit this site (http://www.ucl.ac.uk/residences/) for more details and to make any accommodation bookings. We advise booking early. The accommodation is basic, but clean and fantastic value for London.
For something a bit grander we recommend the Cartwright Gardens Apartments:
Page last modified on 23 apr 15 11:50