Profiling Burglary in London using Geodemographics. Chris Gale 1, Alex Singleton 2, Paul Longley 1

Transcription

1 Profiling Burglary in London using Geodemographics Chris Gale 1, Alex Singleton 2, Paul Longley 1 1 2

2 Geodemographic Classifications A Geodemographic Classification: Simplifies a large and complex body of information about a population, where and how they live and work Based on premise that similar people live in similar locations, undertake similar activities and have similar lifestyles and that such area types will be distributed in different locations across a geographical space Clustering algorithms partition demographic data into groups sharing similar characteristics Commercial (such as Mosaic created by Experian and Acorn created by CACI) and free (2011 OAC) classifications available

3 Geodemographic Classifications of London

4 2011 LOAC and coding crime data Coding crime data to the 2011 LOAC Police.UK data from December 2010 to July 2014 Burglary the only crime category used

5 2011 LOAC and coding crime data Assignment of different 2011 LOAC Supergroups to Output Areas in London

6 2011 LOAC and coding crime data Road network overlaid on the 2011 LOAC Supergroups

7 2011 LOAC and coding crime data Police.UK reported crime centroids added (for 4 million crime events)

8 2011 LOAC and coding crime data 94,667 Voronoi polygons created based on reported crime centroids Provides an estimation of the geography used to report crime on Police.UK

9 Assigning crime events to the 2011 LOAC Two methods of attributing reported crime events to 2011 LOAC Supergroups tested: Centroid location Proportional assignment

10 Example of centroid location method 100 burglary events assigned to centroid = 100 burglary events assigned to High Density and High Rise Flats

11 Example of proportional assignment method 100 burglary events assigned to centroid = 80 burglary events assigned to High Density and High Rise Flats

12 Example of proportional assignment method 100 burglary events assigned to centroid = 20 burglary events assigned to City Vibe

13 Assigning crime events to the 2011 LOAC Only small differences between the two methods However, if fewer crime event records and/or a smaller geographic area of study then greater discrepancies between the two methods are likely 32 BOROUGHS OF LONDON Recorded crimes based on centroid locations Recorded crimes based on proportional assignment Difference A: Intermediate Lifestyles 10.25% 10.26% 0.02% B: High Density and High Rise Flats 13.88% 13.56% -0.31% C: Settled Asians 11.38% 11.09% -0.28% D: Urban Elites 16.36% 16.51% 0.16% E: City Vibe 15.28% 15.48% 0.20% F: London Life-Cycle 8.69% 8.52% -0.18% G: Multi-Ethnic Suburbs 18.34% 19.10% 0.76% H: Ageing City Fringe 5.84% 5.47% -0.36%

14 Index Scores of burglary rates by 2011 LOAC Supergroup Score of 100 equates to London s 2010 to 2014 average of 98 burglaries being committed per 1,000 dwellings

15 MPS Neighbourhood Classification Built by the GLA Based on the 2011 OAC methodology Uses a different geography and 99 variables (from the 2011 Census and the London Datastore Ward Atlas)

16 Public Attitude Survey (PAS) Used to elicit the public s perceptions of policing needs, priorities and experiences with the Metropolitan Police Service (MPS) 21 questions used to measure public confidence in the MPS 33 to 34 interviews carried out per month per Borough

17 Neighbourhood Confidence & Crime Comparator Interactive web-tool built visualising the 12 MPS Neighbourhood Classification clusters, Public Attitude Survey data and crime data Overall confidence in the MPS across London

18 Neighbourhood Confidence & Crime Comparator MPS Neighbourhoods assigned to the Single- Living Centre cluster Overall confidence in the MPS

19 Neighbourhood Confidence & Crime Comparator MPS Neighbourhoods assigned to the Settled Multi-Ethnic cluster Overall confidence in the MPS

20 Neighbourhood Confidence & Crime Comparator MPS Neighbourhoods assigned to the Crowded Outer Suburbia cluster How well do the MPS communicate?

21 Neighbourhood Confidence & Crime Comparator MPS Neighbourhoods assigned to the Stressed Urban cluster How well do the MPS understand issues that affect the community?

22 Neighbourhood Confidence & Crime Comparator MPS Neighbourhoods assigned to the Single- Living centre cluster Overall crime rate

23 Summary Profiling Police.UK data with the 2011 LOAC is an example of using geodemographics to derive insight from open data sources MPS Neighbourhood Classification and Neighbourhood Confidence & Crime Comparator are examples of creating bespoke geodemographic applications to contextualise public confidence in the police and crime levels in London

24

25

26 geogale.github.io/2011oac

27 oac.datashine.org.uk

28 plus.google.com/u/0/communities/

29 Thank You This work was supported by EPSRC grants EP/J004197/1 (Crime, policing and citizenship (CPC) - space-time interactions of dynamic networks) and EP/J005266/1 (The uncertainty of identity: linking spatiotemporal information between virtual and real worlds) and ESRC grants ES/K004719/1 (Using secondary data to measure, monitor and visualise spatio-temporal uncertainties in geodemographics) and ES/L011840/1 (Retail Business Datasafe).