Mapping and correlating
crime/ASB and Private Sector
Housing Using the Gi* Statistic
Sophie Curtis-Ham
Senior Community Safety Analyst
London Borough of Newham
Sophie.Curtis-Ham@newham.gov.uk
Maps
Copyright
All maps based on Ordnance Survey material with the permission of Ordnance Survey. ©
Crown Copyright and database rights 2012 Ordnance Survey 100019272.
Overview
1. The legal context and purpose of analysis
2. Data
3. Method
4. Outcomes
The legal context and purpose of analysis
• Purpose: whether and where to apply a scheme for
licensing Private Rental Sector (PRS) landlords.
• Legal question: A Local Authority can implement landlord
licensing where PRS housing is found to be contributing to
ASB, in order to better control the behaviour of tenants by
regulating landlords.
• Analytical questions: Is there a correlation between the
locations of PRS housing and hotspots for relevant types
of crime and ASB? Where are there high levels of PRS
and crime/ASB?
The legal context and purpose of analysis
• Purpose: whether and where to apply a scheme for
licensing Private Rental Sector (PRS) landlords.
• Legal question: A Local Authority can implement landlord
licensing where PRS housing is found to be contributing to
ASB, in order to better control the behaviour of tenants by
regulating landlords.
• Analytical questions: Is there a correlation between the
locations of PRS housing and hotspots for relevant types
of crime and ASB? Where are there high levels of PRS
and crime/ASB?
Data
• Met Police CRIS offences
• ‘UNI-form’ council ASB records
• CAD 999 callouts for ASB
}
• Map layer with locations of PRS
housing premises
Categories:
• most relevant to
the Housing Act
definition.
• most likely to
relate to tenants’
behaviour in the
premises
• accessible from
existing
databases
Data
• Met Police CRIS offences
• ‘UNI-form’ council ASB records
• CAD 999 callouts for ASB
}
• Map layer with locations of PRS
housing premises
Categories:
• most relevant to
the Housing Act
definition.
• most likely to
relate to tenants’
behaviour in the
premises
• accessible from
existing
databases
Method - overview
• Met Police CRIS offences
• ‘UNI-form’ council ASB records
• PRS housing locations
• CAD 999 callouts
}
Point data
Gi* mapping based
on cell counts in grid
with 75m x 75m cells
Points and 250m grid ‘centroids’
Gi* based on cells counts in grid
with larger 250m x 250m cells
Method – Gi* statistic – WHY?
Objectivity
Statistical significance
Predictive accuracy/reliability
Mapping overlays
Correlation analysis
Method – Gi* statistic – WHY?
Objectivity
Statistical significance
Predictive accuracy/reliability
Mapping overlays
Correlation analysis
Method – Gi* statistic – HOW?
Calculating the Gi* statistic
MapInfo
ArcGIS
Create grid
Create grid
Count incidents per grid
Join data to grid to
cell
Export to Excel
Run Gi* in Rook’s case
create count of
incidents per grid cell
Run Gi* in Arc
Gi* z-score per grid cell. Scores ≥ 1.960 are statistically
significant at p<.05 level
Method – Gi* statistic – HOW?
Mapping the Gi* hotspot overlaps
1. Create a column or use queries to indicate the cells
with significant scores for ASB AND PRS datasets, i.e.
the overlapping cells.
2. Show these cells on the map to indicate the
overlapping areas.
Outcomes – Gi* overlap areas - example
PRS premises
Rowdy behaviour etc
+
PRS significant
clustering only
=
ASB type significant
clustering only
Both PRS and ASB
type significant
clustering
Outcomes – Gi* overlap areas - individually
Waste in front gardens
Noise complaints
PRS properties
PRS significant
clustering only
ASB type significant
clustering only
Both PRS and ASB
type significant
clustering
Burglary - dwelling
CAD ASB
Outcomes – Gi* overlap areas - cumulatively
All ASB Types (excluding CAD)
PRS properties
PRS significant
clustering only
All ASB types
significant clustering
only
Both PRS and any
ASB significant
clustering
Outcomes – Correlation analysis
Cell
number/
ref
PRS
Count
PRS Gi*
z-Score
ASB Rowdy
Count
ASB –
Rowdy
Gi*
Score
1
0
0.05
0
0.1
2
0
0.6
1
2.4
3
1
1.4
3
3.1
4
5
1.7
3
5.6
5
7
5.3
9
7.5
6
0
1.4
1
2.3
7
4
8.4
0
2.1
8
2
1.7
3
1.6
9
0
0.01
0
0.3
Statistical test
Pearson's r (parametric)
Spearman's rho (non-parametric)
Grid cell count
Gi* z-score
Correlation coefficient P-value Correlation coefficient P-value
.476
.000
.783
.000
.721
.000
.865
.000
Outcomes – Correlation checks
Areas of land excluded from further correlation checks
PRS properties
Excluded areas
Outcomes – Implementation
• Borough wide landlord licensing imposed
• All 35000 properties to be licensed by 31 January 2013
• Estimated 14000 will fail to be licensed on time
Warning letters
Estimated 5000 unlicensed ‘hardcore’
Anticipated 500-800 prosecutions per year
Cultural shift in landlord behaviour towards compliance and
better property management
Reduction in poor management and ASB issues
QUESTIONS?