Prospective crime mapping in operational context Final report

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Figure 6.4: Changes in the proportion of burglaries committed during the daytime over time (forevents for which the interval between the earliest and latest reporting times was less than 8 hours)0.700.60Proportion of all burglaries0.500.400.300.200.10BeforeDuringLinear (Before)0.00MonthDec-05Aug-05Apr-05Apr-03Dec-02Aug-02Apr-02Dec-01Aug-01Apr-01Dec-04Aug-04Apr-04Dec-03Aug-03Considering the changes in the comparison area, as shown in Figure 6.5 there was also observed areduction in the proportion of burglaries committed during the evening, although the change over timewas not as distinct (means = 0.24 and 0.17, SDs = 0.11 and 0.05, N=52 and 7, respectively) as for thepilot area and in the comparison area the trend was more similar to the historic trend, particularly ifone takes account of the outlying observation in July.As a further analysis, and to take account of seasonality, the proportion of burglaries committed duringthe evening for the pilot interval (August 2004 to February 2005) and for the same period for the yearbefore (August 2003 to February 2004) were compared for both pilot and comparison areas. For thepilot area the proportion was lower during implementation (mean=0.11, SD=0.04, N=7) than for thesame period the year before (mean=0.17, SD=0.07, N=7), a difference which achieved statisticalsignificance (z=2.03, p
Figure 6.5: Changes in the proportion of burglaries committed during the evening over time (forevents for which the interval between the earliest and latest reporting times was less than 8 hours)0.600.50BeforeDuringLinear (Before)Proportion of all burglaries0.400.300.200.100.00MonthApr-03Dec-02Aug-02Apr-02Dec-01Aug-01Apr-01Dec-05Aug-05Apr-05Dec-04Aug-04Apr-04Dec-03Aug-03The above results, which show a selective pattern, are certainly in line with what would be expected ifthe system had been used most frequently during the evening and was helpful in reducing burglary.However, to provide a more conclusive result, data for a longer period of time during whichimplementation occurred would be required to demonstrate continuation of the observed trend. Inparticular, this would further help to rule out any seasonal effect. Thus, it is suggested that the resultshown is enticing but inconclusive.As discussed at the start of this section, detailed analyses were conducted to explore changes overtime in the spatial and spatio-temporal distribution of burglary. For reasons already discussed, theseanalyses are presented in Appendix 3.66
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1. UCL JILL DANDO INSTITUTE OF CRIM
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ContentsAcknowledgementsExecutive s
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2.5 Illustration of a simple neares
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Project outcomesPatterns of burglar
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those that involved collaboration w
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1. IntroductionThis report represen
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optimally calibrated system, the go
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e ij = n .j x n i.nWhere, e ij is t
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Table 2.2: Knox ratios for Mansfiel
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Table 2.6: Monte-Carlo results for
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Table 2.10: Weekly Knox ratios for
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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
Page 59 and 60: Figure 5.1: Promap dissemination pr
Page 61 and 62: the busy schedule of the new Divisi
Page 63 and 64: Tactical deliveryCommand Team daily
Page 65 and 66: Table 5.3: Number of respondents wh
Page 67 and 68: permitted, up to four plain clothed
Page 69 and 70: observation made by those who used
Page 71 and 72: A simple time-series analysis (see
Page 73 and 74: Two approaches were used to compute
Page 75: Figure 6.3: Changes in the proporti
Page 79 and 80: With respect to implementation real
Page 81 and 82: ReferencesAggresti, A. (1996) An In
Page 83 and 84: Johnson, S.D., Summers, L., and Pea
Page 85 and 86: Appendix 1. The information technol
Page 87 and 88: Figure A1.2: Stand-alone applicatio
Page 89 and 90: Recommendations that may be realise
Page 91 and 92: Section 1: knowledge and understand
Page 93 and 94: Extra Comments (please outline any
Page 95 and 96: In relation to the evaluation of in
Page 97 and 98: Time-series analysisFor the purpose
Page 99 and 100: Figure A3.1: Changes in the spatial
Page 101 and 102: Figure A3.2: Lorenz curves showing
Page 103 and 104: To recapitulate and elaborate, the
Page 105 and 106: Concluding comments on methodThe te
Page 107 and 108: Figure A5.2: An enlargement of the
Page 109 and 110: Figure A5.6: Prospective map magnif
Page 111: Produced by the Research Developmen
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