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Systematic review and meta-analysis of risk terrain modelling (RTM) as a spatial forecasting method

Authors
  • Marchment, Zoe1
  • Gill, Paul1
  • 1 UCL, London, England , London (United Kingdom)
Type
Published Article
Journal
Crime Science
Publisher
Springer Berlin Heidelberg
Publication Date
Jun 16, 2021
Volume
10
Issue
1
Identifiers
DOI: 10.1186/s40163-021-00149-6
Source
Springer Nature
Disciplines
  • Systematic Review
License
Green

Abstract

BackgroundSeveral studies have tested the reliability of Risk Terrain Modelling (RTM) by focusing on different geographical contexts and types of crime or events. However, to date, there has been no attempt to systematically review the evidence on whether RTM is effective at predicting areas at high risk of events. This paper reviews RTM’s efficacy as a spatial forecasting method.MethodsWe conducted a systematic review and meta-analysis of the RTM literature. We aggregated the available data from a sample of studies that measure predictive accuracy and conducted a proportion meta-analysis on studies with appropriate data.ResultsIn total, we found 25 studies meeting the inclusion criteria. The systematic review demonstrated that RTM has been successful in identifying at risk places for acquisitive crimes, violent crimes, child maltreatment, terrorism, drug related crimes and driving while intoxicated (DWI). The proportion meta-analysis indicated that almost half of future cases in the studies analysed were captured in the top ten per cent of risk cells. This typically covers a very small portion of the full study area.ConclusionsThe study demonstrates that RTM is an effective forecasting method that can be applied to identify places at greatest risk of an event and can be a useful tool in guiding targeted responses to crime problems.

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