Prospective crime mapping in operational context Final report

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Project outcomesPatterns of burglaryUsing a modification of an approach developed in the field of epidemiology, analyses wereconducted to see if burglary does cluster in space and time and if the patterns vary acrosslocation. Briefly, to do this, for each area each burglary event is compared to every other andthe space-time distance between them recorded. The pattern of results observed is thencompared with what would be expected on the basis of chance, determined using what isknown as a Monte-Carlo simulation. Burglary was considered to be communicable if moreevents occurred near to each other in both space and time than would be expected on thebasis of chance.Without exception in the East Midlands areas studied, the risk of burglary is communicable upto a distance of around 400m for at least one month. This finding was used as a general rulein the construction of basic prospective maps. Sensitivity analyses were conducted toexamine the duration of the elevation in risk. These suggested that risk (albeit diminishing)extended beyond one month and in most cases up to around eight weeks.The patterns were to some extent specific to the time of day considered. For example, if aburglary occurred at one location during the afternoon, a further burglary was more likelynearby soon after and at a similar time of day. In supplementary work not reported here, theftfrom (but not theft of) vehicles was also found to be communicable.Developing the predictive system and measuring its accuracyOn the basis of the above findings, a method of prospective mapping (hereafter, Promap),based on the authors’ previous work, was developed. Across the different areas studied inthe initial phase of the research, police analysts were already using descriptive hotspotmapping. Promap was tested against an optimised version of the ‘retrospective’ hotspottingmethod in current use. The optimised versions were substantially more predictive than mapswhich resemble those typically used in crime analysis. Promap outperformed the optimised‘retrospective’ hotspot mapping system. It did this in three ways.• Promap correctly predicted more burglaries than other methods. For example, the finalversion of Promap could identify the locations of 78 per cent burglaries that occurredwithin the next seven days of a forecast, whereas for the same interval theretrospective model could identify only 51 per cent.• Relative to the retrospective maps, it yielded hotspots which formed more solid,coalescent, hence readily patrollable, areas.• The final version of Promap accurately predicted more crime while identifying a smallerarea than other methods. For example, the same fraction of burglaries occurring withintwo to seven days of a prediction could be forecasted by identifying patrolling areas halfthe size of those generated by retrospective mapsImplications for operational policingResearch conducted by the authors and others suggests that police officers’ perceptions ofwhere burglary hotspots form are often imperfect. This is particularly true for recent ratherthan enduring problems. The fluidity of burglary risk provides an explanation for this. Crimemoves and patterns evolve. Why should police officers be able to anticipate such changes?They should not, but computerised support systems that can assist in the crime reductionenterprise should.The advantages of Promap are that it could act to facilitate more targeted crime reductioninterventions, increasing the likelihood that resources are deployed to the right places at theright time, rather than where they were needed last week or last month (as with conventionalhotspot methods). Risky areas can be better defined so that patrols could move throughpriority areas more efficiently, spending less time in places with lower risk. The maps can alsobe produced for specific shifts to ensure their continued relevance over the course of the day.vi
Developing predictive mapping in an operational policing contextSupport systems are only valuable if they can be used and understood by those operatingthem. Promap software was developed for use in one police Basic Command Unit (BCU) inthe East Midlands in consultation with local police and community safety practitioners. Usingthe software, maps could easily be produced at regular intervals by crime analysts, discussedduring shift briefings and provided to beat officers. The maps clearly defined the areas withthe highest predicted risks, against a background of the housing distribution and significantgeographical points of reference, which could then be used as guides to patrolling. Inresponse to feedback, different maps were generated for each of the three police shifts of theday.The system was modified in response to practitioner requests. Considerable effort wasexpended to optimise the algorithms used to ensure that the system could generate mapsrapidly. The final version could generate maps for the entire participating BCU in around 20seconds. A different system which generates descriptive (i.e. not predictive) maps, took tenminutes to complete an analysis of the same area, with extra time required to display theresulting output.Issues of implementation encountered in situFollowing consultation with the staff in the pilot BCU and their crime reduction partners, thesystem was modified and used in an operational context over a period of six months.Promaps were generated for each of five sections which comprised the BCU by crimeanalysts located at police headquarters, and disseminated using the force IT system.A process evaluation was conducted over the implementation period to see how the systemwas used. This involved observation of briefing meetings, a log of the tactical options used inresponse to the maps, and a survey of front-line police officers.Issues with system implementation• Despite the fact that the system itself was considered simple to use, changes of keypersonnel (including the BCU commander) and force IT requirements (which initiallyrendered the system unnecessarily complex) made for a slow start. Those surveyedcame to regard it as useful to the point of enquiring about the possibility of its extensionto cover other crime types.• Timely dissemination of relevant maps to front-line officers was a source of initialdifficulty, resolved to general satisfaction distressingly late in the pilot period. At firstthere were issues with the physical transfer of maps from the crime analysts, located atpolice headquarters, to the staff throughout the BCU. The maps were initially generateddaily but beat officers felt that there were only minor changes in the maps whengenerated with this frequency. Eventually, these issues were partially resolved byproviding local staff access to the mapping software, and by producing the maps twicea week. Implementation issues of this kind currently represent one of the mostimportant limiting factors in prospective mapping utility, but their resolution is mostly amatter of ensuring that basic IT infrastructure is adequately configured, and the systemis not hobbled by adherence to IT custom and practice.• Part of this project involved a review of possible tactical options that could be used inconjunction with the new maps. These ranged from well-established anti-burglaryinitiatives, such as target hardening and police patrols to novel techniques suggested inthe light of the burglary patterns found. The review of each technique includeddocumented success or failure, financial costs, and the speed with whichimplementation was plausible, swiftness of implementation being important in thecurrent project.It appeared that the most favoured methods were those that combined the maps withother local intelligence (such as data on known offenders) to direct police patrols, andvii
Page 2 and 3: 1. UCL JILL DANDO INSTITUTE OF CRIM
Page 4 and 5: ContentsAcknowledgementsExecutive s
Page 6 and 7: 2.5 Illustration of a simple neares
Page 10 and 11: those that involved collaboration w
Page 12 and 13: 1. IntroductionThis report represen
Page 14 and 15: optimally calibrated system, the go
Page 16 and 17: e ij = n .j x n i.nWhere, e ij is t
Page 18 and 19: Table 2.2: Knox ratios for Mansfiel
Page 20 and 21: Table 2.6: Monte-Carlo results for
Page 22 and 23: Table 2.10: Weekly Knox ratios for
Page 24 and 25: Table 2.14: Monte-Carlo results for
Page 26 and 27: Figure 2.1: The five policing areas
Page 28 and 29: The results for area 5 again demons
Page 30 and 31: The bandwidth used to generate the
Page 32: a densely populated urban area this
Page 35 and 36: Table 2.24: Average number of crime
Page 37 and 38: Patrolling efficiencyAs discussed e
Page 39 and 40: 3. Tactical options and selecting a
Page 41 and 42: Selecting a pilot siteThe decision
Page 43 and 44: Table 3.2: Tactical options matrixT
Page 45 and 46: Type ofinterventionStudyUse ofintel
Page 47 and 48: Other potential tactical optionsAt
Page 49 and 50: 4. System development and evolution
Page 51 and 52: the same time of day as each other
Page 53 and 54: unfortunately, implementation or us
Page 55 and 56: any tactical options were employed
Page 57 and 58: the end of the pilot. In addition t
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Figure 5.1: Promap dissemination pr
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the busy schedule of the new Divisi
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Tactical deliveryCommand Team daily
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Table 5.3: Number of respondents wh
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permitted, up to four plain clothed
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observation made by those who used
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A simple time-series analysis (see
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Two approaches were used to compute
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Figure 6.3: Changes in the proporti
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Figure 6.5: Changes in the proporti
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With respect to implementation real
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ReferencesAggresti, A. (1996) An In
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Johnson, S.D., Summers, L., and Pea
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Appendix 1. The information technol
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Figure A1.2: Stand-alone applicatio
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Recommendations that may be realise
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Section 1: knowledge and understand
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Extra Comments (please outline any
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In relation to the evaluation of in
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Time-series analysisFor the purpose
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Figure A3.1: Changes in the spatial
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Figure A3.2: Lorenz curves showing
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To recapitulate and elaborate, the
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Concluding comments on methodThe te
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Figure A5.2: An enlargement of the
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Figure A5.6: Prospective map magnif
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Produced by the Research Developmen
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Prospective crime mapping in operational context Final report

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