Thames Gateway Crime and
Thames
Gateway
Design Project
Crime and Design Project
Mapping neighbourhood
vulnerability to street crime
3rd National Crime Mapping
andConference
burglary
Context
•
Thames Gateway represents the largest and most ambitious
regeneration project in Europe.
•
91,000 homes and 150,000 jobs
•
unique city-building opportunity.
•
exemplar of the standards and principles of sustainability, cohesion
and liveability expected by the government across the UK
•
high levels of crime, or simply the fear of crime, will make the benefits
of regeneration inaccessible or unsustainable.
•
principles of successful community and neighbourhood development
should be built into the regeneration process from the very start.
•
once new communities are established it will be difficult to rectify
problems and try to address community and design issues later.
The Crime and Design Project
3 strands building towards development policy and practice
1.
2.
3.
Theme guide – a regeneration
framework to inform development of
project briefs, project appraisal and
evaluation, decision making, for the
development of housing, open
space, town centres etc
Concordat – a base-level
agreement between built
environment practitioners and the
police to work closer together and in
the early stages of a development
proposal
Mapping project – analysing crime
data at a neighbourhood level to
ascertain what environmental and
socio-economic attributes count as
factors in the vulnerability of
neighbourhoods to crime
Critical Questions:
•
What makes a “good” neighbourhood?
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Why are some neighbourhoods more vulnerable to crime than others?
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Are there environmental and social factors that contribute to a
neighbourhood’s vulnerability?
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Can we isolate those factors which contribute more than others?
•
How perceptive are environmental variables?
•
Can we develop rules or patterns that govern vulnerability to certain
types of crime?
•
Can these rules in turn inform planning and design solutions to
effectively remove them?
•
What will be the impact of this on the ability to develop sustainable
communities?
Mapping neighbourhood vulnerability
Considers 3 groups of ideas underpinning the propensity for crime in
neighbourhoods and uses them as a starting point to test the following
statements:
1. Areas will not regenerate if people are not attracted to them.
Neighbourhood satisfaction is judged by resident’s perception of
cleanliness, vandalism and crime levels. Has an effect on the attractiveness
of a neighbourhood to potential new residents. (broken windows)
2. Lively environments are safer environments.
Environments that have been designed with safety and crime reduction in
mind are more successful places because they build in overt control and
management of spaces to a distinct group of users. (defensible space)
3. Cohesive communities are self-policing.
Developments that have considered the impacts of design on the people
that use them and have catered for their needs with correct level of facilities
will lead to more cohesive communities. (social efficacy)
Thames Gateway London Deprivation
Thames Gateway London boroughs
Dependent variables
•
analysed 2 dependent crime variables across
the Thames Gateway :
i.
annual rate of street crime per kilometre of
street
ii.
annual rate of domestic burglary per
thousand households.
•
*Note: Street crime does not include anti-social
behaviour
•
Presented at Census Output Area (COA) level
•
Separate from IMD crime dimension which
looks at all types of crime
Independent variables
•
30 independent variables selected
•
identified in literature as being
essential for developing cohesive
communities
•
suggests that physical planning,
management of the fabric and social
composition all play a part?
•
14 variables from the census
•
11 represent distances to a range of
facilities
•
calculated as shortest distance from
each postcode
Environmental
Variable
Description
Source
Vacancy
Proportion vacant properties
ONS
Deliveries
Non-domestic deliveries as a proportion of total deliveries
OS
Dentist
average weighted distance to a dental practice
TGLP
GP
average weighted distance to a GP practice
TGLP
Pharmacy
average weighted distance to a pharmacy
TGLP
Police
average weighted distance to a police station
MPS
Rail
average weighted distance to a rail/underground station
TFL
Post Office
average weighted distance to a post office
Royal Mail
Town Centre
average weighted distance to a town centre
OPDM
Newsagent
average weighted distance to a newsagents or store
Yell.com
School
average weighted distance to a primary school
boroughs
Open space
average weighted distance to open space
Green Grid + Bartholemew
Bus
average weighted distance to a bus route
TFL
Density
Residential density per hectare from buffered postcodes
ONS + OS
Street length
Average length of street section
Bartholemew
Street density
Street density metres per hectare
Bartholemew + OS
Socio-Economic
Variable
Description
Source
Ethnic minority
Proportion ethnic minority
ONS
Female lone parents
Female lone-parents as proportion of households with dependent children
ONS
Foreign born
Proportion foreign born
ONS
Social grade
Proportion social grade C2 to E
ONS
Young people
Proportion population aged 15-24
ONS
Low qualifications
Proportion population with qualifications < Level 3
ONS
Low qualified young
people
Young people 18-24 with qualifications < Level 3 as proportion of age
group
ONS
Religious minority
Proportion of population religious minority
ONS
Unemployed
Proportion of economically active that unemployed
ONS
Carers
Proportion of population providing unpaid care
ONS
Turnover
Residents not at this address in previous year as proportion of total
population
ONS
Migration
Net migration as a proportion of total population
ONS
IMD score
Interpolated IMD 2004 from Super Output Area Centroids
ODPM
Renting
Proportion rented accommodation
ONS
Analysis: Correlations
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•
•
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Spearman rank correlations:
1. street crime: some strong positive and negative
2. burglary: weaker correlations and two variables (vacant dwellings
and open space) are not significant.
correlations >=+0.2 or <= -0.2 qualified for a factor analysis
exploratory factor analysis for each crime type to weed out variables
with low factor scores
5 factors/dimensions were identified for each crime type, broadly
similar but ordered differently
Analysis: Regression
Exercise in isolating the most significant variables using increasingly
detailed regressions until the most significant variables are isolated:
1. Create indices to represent the 5 dimensions
2. Comprise the factors with the highest scores
3. Regression tests the correlation between indices and the crime
variables
4. Results are run through an induction programme to generate
decision trees for each crime type
5. first time that these type of decision trees have been derived for
crime types at the neighbourhood level
Analysis: Decision trees
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•
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Measuring characteristics of vulnerability
Depending on degree of significance, the indices generate different
sets of relationships
Gives rise to a probability for crime according to branches followed
splits in the tree reflect the multiple correlation scores
Helps us to identify most significant LOCAL factor(s)
Can then work towards designing/managing them out
Example: Street crime decision tree
Some findings:
•
Closer a neighbourhood is to a facility/service the greater risk of
burglary
•
Shorter the street the lesser the risk of burglary
•
Greater the street density the greater risk of street crime
Supports defensible space theories
However!!!!!!
• Physical factors explain only <50%
of the story
•
Reinforces idea that environmental
design alone can only do so much
•
has to be supported by people
management
Street Crime 2002: Neighbourhoods rates at Census Output Area level
Household Burglary 2002: Neighbourhoods rates at Census Output Area level
Distances to community facilities
Street crime
•
Immigrant/minority groups is the most
important dimension for street crime
•
followed by deprivation/exclusion and low
order centrality.
•
*Note: not saying that these are the groups
engaged in crime
•
this dimension is a proxy for:
– there is segregation between minority
groups within a neighbourhood?
– these areas have more restricted life
chances?
– lack of assimilation into mainstream
society?
– difficulty in engaging with agencies?
Implications:
• Reinforces literature that states community efficacy is
one of the most important factors in creating sustainable
and safer communities
• Reinforces validity of government’s programme for social
exclusion
• Highlights importance of providing adequate access to
facilities in the neighbourhood
• Supports the idea that crime is a determined by local
factors and must be tackled through local interventions
• Can use the model to evaluate new masterplans in the
Thames Gateway
• Help determine the optimum range and siting of facilities
to develop neighbourhoods with sufficient strength to
reduce vulnerability to crime