Improving police practice and reducing the incidence of crime through mapping and analysis
Submitting InstitutionUniversity College London
Unit of AssessmentSocial Work and Social Policy
Summary Impact TypeLegal
Research Subject Area(s)
Studies In Human Society: Criminology
Summary of the impact
Research on spatial patterns of crime at UCL has influenced police
practice and has informed policy and its implementation in countries
including Australia, Canada, UK, and USA. Our research has challenged
conventional wisdom amongst police and policymakers about spatial patterns
of crime. Working directly with police forces and through our continuing
professional development training, we have spearheaded the use of crime
mapping and forecasting methods in practice. Implementation has led to
documented reductions in crimes such as burglary of between 20-66%.
Research at UCL Security & Crime Science (SCS) concerns the
identification and explanation of regularities in spatial and space-time
patterns of crime and how their identification can be used to reduce
crime. Research on spatial patterns of crime began when Spencer Chainey
joined the department (part of the UCL Jill Dando Institute of Crime
Science) in 2003. Research on space-time] patterns commenced in 2004 when
Professors Kate Bowers and Shane Johnson arrived.
Between 2004 and 2009, Johnson and Bowers led a British
Academy-funded international collaboration between researchers at UCL, the
Netherlands Centre for the study of Crime and Law Enforcement (Amsterdam,
Netherlands), and Temple University (Philadelphia, USA) to study
space-time patterns of crime in different countries. The research showed
that across cities in five different countries (see [a] in section 3) the
risk of burglary spreads in space and time much like a disease, with a
regularity that makes it amenable to prediction. Further research,
conducted as part of this collaboration showed that this extended to
improvised explosive device (IED) attacks in Iraq. Departmental research
has shown this to be the case for a range of other crime types including
theft from motor vehicles, cash in transit robbery, riots, and even
maritime piracy. With respect to burglary, we demonstrated that novel
predictive models based on our findings outperform alternative methods
[b]. And, with a view to assessing the utility of predictive approaches
more generally, we conducted the first reviews of the predictive accuracy
of traditional methods of crime mapping [c], and showed that — in contrast
to conventional wisdom — geographically focused police initiatives do not
displace crime [d].
Underlying the research on the space-time dynamics of crime, and the
forecasting method developed, is the hypothesis — developed at UCL — that
offenders adopt `foraging' strategies at least some of the time, seeking
to maximise the benefit of their activity whilst minimising search time
and associated risks [b, e]. As such, burglars (for example) are predicted
to return to previously victimised homes/locations (repeat victimisation)
when the benefits outweigh the risks, and nearby places that share similar
characteristics (near repeat victimisation). With further British Academy
funding (2007-2008) Johnson directed a study that used computer
simulation, quantitative and qualitative methods to test this hypothesis.
The analysis of crimes detected by the police [e] facilitated the study of
patterns of observed offender spatial choices; computer simulation (e.g.
[f]) — a generative modelling approach which allows theoretical models to
be formalised and tested in silico — was used to test and assess competing
theories; and, qualitative research interviews with offenders provided a
"bottom-up" approach to further develop understanding of offender spatial
decision-making. The findings, generated using very different research
methods that are rarely used together, support the offender as forager
hypothesis and provided insights relevant to the crime reduction
References to the research
Researchers at SCS (at the time of research and publication) are listed
in bold. All publications have been through rigorous peer review.
[a] Johnson, S. D., Bernasco, W., Bowers, K. J., Elffers,
H., Ratcliffe, J., Rengert, G., & Townsley, M. (2007).
Space-Time Patterns of Risk: A Cross National Assessment of Residential
Burglary Victimization. J. of Quant. Criminol, 23, 201-219. DOI:
Cited 94 times (Google Scholar); 3rd most cited article in journal
published since 2007. Consistently a top 5 Criminology and Penology
journal (ISI Web of Knowledge).
[b] Johnson, S. D., Bowers, K. J., Birks, D. and
Pease, K. (2009). Predictive Mapping of Crime by ProMap, Weisburd,
D., W. Bernasco and G. Bruinsma (Eds.) Putting Crime in its Place: Units
of Analysis in Spatial Crime Research, New York: Springer. (Available upon
[c] Chainey, S., Tompson, L., & Uhlig, S. (2008). The
Utility of Hotspot Mapping for Predicting Spatial Patterns of Crime. Security
Journal, 21, 4-28. DOI: 10.1057/palgrave.sj.8350066.
Cited 65 times (Google Scholar), and the 3rd most cited article in
Security Journal since 2007.
[d] Bowers, K.J., Johnson, S.D., Guerette, R.T., Summers,
L., & Poynton, S. (2011). Spatial Displacement and Diffusion of
Benefit Among Geographically Focused Policing Initiatives: A
Meta-Analytical Review, J. Exp. Criminol., 7(4), 347-374. DOI:
[e] Johnson, S. D., Summers, L., & Pease, K.
(2009). Offender as forager? A direct test of the boost account of
victimization. J. Quant. Criminol. 25(2), 181-200. DOI: 10.1007/s10940-008-9060-8.
Cited 41 times (Google Scholar) and the 5th most cited article in
journal since publication in 2009.
[f] Johnson, S. D. (2008). Repeat Burglary Victimization: A Tale
of Two Theories. J. Exp. Criminol., 4, 215-240. DOI: 10.1007/s11292-008-9055-3.
Cited 39 times (Google Scholar); 5th most cited article published
in journal since 2008.
Key peer-reviewed grants
`Predicting Patterns of Criminal Activity' British Academy International
Collaborative Activities Network Grant. PI: Professor Shane Johnson.
Amount £13,150. Duration Feb 2004-Dec 2008. Outputs from this grant: [a],
'Offender Targeting Decisions for Acquisitive Crime' British Academy
Large Grant. PI: Professor Shane Johnson. Amount: £62,613. Duration May
2007-Oct 2008. Outputs from this grant: [e], [f].
`Campbell collaboration systematic review on spatial displacement among
geographically focused policing initiatives' National Policing Improvement
Agency grant. PI: Professor Kate Bowers. Amount $46,363. Duration: Nov
2009-April 2010. Output from this grant [d].
Details of the impact
For a long time, police responses to crime reduction have focused on
catching offenders. This is partly due to the perception that the timing
and location of crime events is not predictable and, even if it were, the
police and others have commonly questioned the idea that place-based
strategies actually reduce crime, assuming that crimes prevented at one
location will simply be `displaced' to others. More generally, the
practical value of academic research in policing has often been questioned
by practitioners. However, our research on crime prediction has shown that
prediction is possible and practicable, our systematic review of research
concerned with crime displacement has dispelled the myth that place-based
crime prevention merely displaces crime, and our applied research has
demonstrated the value of academic research in practice.
Through presentations at over 50 practitioner events (including the
Government of Alberta's 2007 international conference on crime reduction,
which informed ), our continuing professional development courses
(over 300 practitioners at 30 courses, 2008-2013), and participation on
advisory boards and direct knowledge transfer activities, our research has
challenged accepted wisdom and substantially influenced policy and
Research has had substantial media coverage, which both reinforces and
demonstrates its influence on discourse. This has included, for example,
articles in the New Scientist (3 May 2008, readership 736k per
issue), on the BBC News website (9 September 2011, >160m page views per
month), and TV coverage on the BBC breakfast news (18 September 2012,
viewership ~1.1m) .
In the UK, research contributions to policy discussion and impact on
police action were recognised at every level. Examples include:
- In May 2012, Chainey was called as expert witness by the
Parliamentary Select Committee on Public Accounts to provide evidence on
the use and impact of online crime mapping for their Implementation of the
Transparency Agenda. His testimony led to the recommendation that they
publish better quality and more useable data .
- An independent report from Her Majesty's Inspectorate of Constabularies
(HMIC) acknowledged SCS research as the basis for pioneering work
employing predictive mapping; a Police Federation article noted our
research has informed police practice; while Johnson's
participation on advisory panels led to an invited contribution in 2012 to
HMIC briefing materials for newly elected Police Crime Commissioners on
what works to reduce crime .
- The UK College of Policing (formerly the National Police Improvement
Agency, NPIA), for whom Johnson contributed to the 2012 NPIA
Masterclass on predictive policing, argue that our work has directly
changed the way the police perform hotspot analyses in practice,
stimulated debate on how this analysis can be effectively used, challenged
conventional wisdom held by those in law enforcement concerning (say)
crime displacement, and informed the future of predictive crime analysis
- Locally, in addition to the changes of practice described below,
Greater Manchester Police note that departmental research has changed
police attitudes to the value of academic research .
The global reach of this influence is demonstrated by:
- Discussion of our research in the 2012 Digest of the International
Association of Crime Analysts (members in 47 countries) focusing on key
academic work on hot-spots policing, and in an Australian Institute of
Criminology (a government agency) brief on using geographical analysis to
prevent crime .
- In the United States, the National Institute for Justice recognised the
importance of our work by funding Professor Jerry Ratcliffe (Temple
University, $95k) to develop "the near repeat calculator"  which
implements some of the algorithms developed as part of our research.
Research at SCS has influenced police practice in the UK and police
forces internationally, as well as community groups concerned with
neighbourhood security. This has led to reduced crime in target
areas, and initiatives have subsequently been extended or imitated
In the UK, based on our research and with support from departmental staff
, Greater Manchester Police (GMP) implemented a predictive mapping
approach to help reduce burglary in Trafford (population 226,578)  in
2010. Predictive maps are used to direct police patrols and, where
feasible, staff from other agencies not usually engaged in crime reduction
(e.g. police driving instructors, and the fire service) to provide
guardianship where (and when) it is predicted to be most needed. This
innovative and successful intervention was recognised by the HMIC as
having scope for wider adoption . Evaluation results  show a 38%
reduction in burglary (471 fewer victims of burglary) in the area of
implementation over a two-year interval. Inspired by departmental research
[e] on other crimes, GMP extended the approach to other high volume
offences, reporting a 29% reduction in theft from motor vehicle
. These projects were recognised internationally: the team were
finalists in the US Goldstein Problem Oriented Policing awards 2012, and
nominated by the Home Office for the 2012 European Crime Prevention
Similar interventions have been implemented elsewhere with comparable
results. For example, in 2012 in North West Leeds (population 321,000),
which had previously experienced the highest burglary rate in the country,
West Yorkshire police reported a 48% decrease in burglary accompanied by
increased public confidence in the police . Other UK police forces
implemented similar approaches in 2008-2013, including Kent, West Mercia,
and the Metropolitan police.
In North Lincolnshire, with Home Office funding and assistance from Johnson,
the Safer Neighbourhoods Team developed the Vigilance Modeller, a software
application based on Bowers and Johnson's early predictive
mapping work. This is used to prioritise areas for crime prevention in
North Lincolnshire (population 167,400) and it was distributed to over 400
community safety partnerships in the UK in 2010. Initially developed for
use by community safety teams (not the police), in 2011 this software was
used by Humberside Police to catch a prolific burglary team .
The reach of these impacts has been expanded overseas both directly and
through research by others. Community safety organisations implemented
successful interventions based on our work.
In Edmonton (Canada) a Neighbourhood Empowerment Team (NET) developed the
Notification of Community Crime (NOCC) intervention to increase community
empowerment to reduce crime. As part of the programme, youth volunteers
visit burglary victims and their neighbours to deliver crime prevention
advice and kits. Following recommendations from departmental research,
teams deliver advice and kits as swiftly as possible. First implemented in
2009, this intervention is ongoing in three NET neighbourhoods and had "a
substantial impact on rates of residential burglary" — e.g. reducing
burglary by 66% in a six-month interval in the Bonnie Doon NET area (pop.
Following invited presentations by Bowers (an update of [b]) and
Johnson (a version of [f]) in Jan 2007, researchers at UCLA
published an article on predictive mapping in 2011 that built on our work
on crime prediction (citing 4 of our papers including [b,f,c] seven times
in the article). This led to a US spin out company (predpol.com) that has
developed commercially available predictive mapping software, grounded in
the principles set out in our research [a,b,e,f]. Their algorithm refined
our approach by incorporating an estimate of the time-stable risk of crime
at locations (discussed in [b,f]) and better calibrating the way in which
the risk of crime is predicted to spread (see [f]). Use of this product by
the police is reported to have resulted in crime reductions of 14% and 27%
respectively in areas of Los Angeles and Santa Cruz .
Sources to corroborate the impact
 Media coverage includes: `Could Predictive Policing Help Prevent
Burglary?' BBC News 18 Sep 2012 (http://bbc.in/1ids6ya)
(2011 page views http://bbc.in/HatvtW
[PDF]); `Sin Cities: What makes some city districts so dangerous?' New
Scientist 3 May 2008 (readership http://bit.ly/HeCJ8H);
`How to get more with less in the police' BBC News 9 Sep 2011 (http://bbc.in/HeCPgL).
 Public Account Committee on transparency (2012)
http://bit.ly/1635PRe; see e.g. Chainey's response to Q26, reflected in
recommendation 2 in the committee's findings: http://bit.ly/HhbkSQ.
 HMIC recognition of research: An advanced police for an advanced
world by Sir Denis O'Connor, Police Federation 2011 (http://bit.ly/17fk2h1
[PDF]); What works in policing to reduce crime, 2012 HMIC online briefing
for Police and Crime Commissioners (http://bit.ly/17IilDa).
 Letter from the UK College of Policing on how our work directly
changed the way police perform hotspot analyses, stimulated debate on the
effective use of this type of analysis, and challenged conventional wisdom
amongst law enforcement practitioners.
 Letter from GMP confirms that their predictive mapping approach was
based on our research and supported by our staff, and that this has led to
substantial reductions in crime; Published evaluation (first 12 months of
implementation): Fielding, M., and Jones, V. (2012). Disrupting the
Optimal Forager: Predictive Risk Mapping and Domestic Burglary Reduction
in Trafford, Greater Manchester. Police Science & Management,
14(1) 30-41 DOI: 10.1350/ijps.2012.14.1.260.
 Australian Institute of Criminology brief on using geography to
reduce crime (June 2008): http://bit.ly/1bep61L.
 Near repeat calculator funded by the US National Institute of
 HMIC recognition of GMP approach: Taking the time for crime: A study
of how police officers prevent crime in the field, 2012 HMIC report (http://bit.ly/18aV9MW
[PDF]); see p. 11-12.
 Statement from North West Leeds police discusses how our research
informed the policing operation "operation optimal" and that this led to
substantial reductions in burglary.
 Statement from North Lincolnshire confirms how our research informed
the development of the vigilance modeller, how this has been used, and the
wide circulation of the modeller in England and Wales; A newsletter
documenting the North Lincolnshire work is also provided (see p. 2).
 Neighbourhood Empowerment Team (NET) intervention, titled the
Notification of Community Crime (NOCC), implemented in Canada at
Edmonton's official blog: http://bit.ly/1eINz22.
 Reason.com article discusses PredPol and the near repeat theory on
which it is based, including link to [a], http://bit.ly/1jc5e2k.
Also see link to Predictive
Policing: The Future of Reasonable
Suspicion in the same article.