Auto Theft & Burglaries Since July 2014 http://youtu.be/gfo8sxPmgRw?list=UUxY2Pkat0Bez7k_SN18TyLQ Home and Commercial Burglaries Since July 2014 http://youtu.be/yZMgXP_Jz1s

1. A
Geospatial Analytic
Presentation
Predictive Criminal Behavior
Albuquerque NM
APD Crime Data
July 2014 - December 2014

2. Null Hypothesis:
There is no correlation between the location
of bus stops and criminal behavior.
Alternative Hypothesis:
The density of criminal
behavior is positively correlated with the
proximity to bus stops.

3. All crimes committed
in ABQ
July 2014 - December 2014

4. Auto Burglary
Spatio-Temporal Model

5. Home Burglary
Spatio-Temporal Model

6. Bus Stops with
1000’ Buffer
Buffer Analysis
• Input Bus Stops Points
• 1000’ foot radius
• Joined the planes

7. Crimes committed
within 1000’
of Bus Stops
Clip Function
• Input Crime Points
• Clip to Bus Stop Buffer

8. Crimes committed
outside 1000’
of Bus Stops
Erase Function
• Input Crime Points
• Erase Bus Stop Buffer
• Result: points outside
• the Buffer

9. Crimes committed
within 1000’ of
Bus Stops
Crimes committed
outside 1000’ of
Bus Stops
Frequency of Distribution
Mean = 5.85
Std Dev = 13.8
N = 3,038
Mean = 4.48
Std Dev = 7.0
N = 1,265

10. Crimes committed
within 1000’ of
Bus Stops
Crimes committed
outside 1000’ of
Bus Stops
Frequency of Distribution

11. Crimes committed
outside 1000’ of
Bus Stops
Average Nearest Neighbor
Calculation
• Input: Points Outside 1000’
• Study area: 710,000 m2
• To determine if clustering or
dispersal of incidents

12. Crimes committed
within 1000’ of
Bus Stops
Average Nearest Neighbor
Calculation
• Input: Points inside 1000’
• Study area: 710,000 m2
• Measures: each point to its
nearest neighbor and averages
the result

13. Crimes committed
within 500’ of
Bus Stops
Average Nearest Neighbor
Calculation
• Input: Points inside 500’
• Study area: 710,000 m2
• Nearest neighbor is most dense
with 500’ of a bus stop

14. Bus Stops with
1000’ Radius

15. Hot Spots
outside 1000’ of
Bus Stops
Optimized Hot Spot
Analysis
• Input: Points outside 1000’
• Count: Events outside
• clipped polygons
• Finds: Density of surface
points

16. Hot Spots
within 1000’ of
Bus Stops
Optimized Hot Spot
Analysis
• Input: Points Inside 1000’
• Count: Events inside
clipped polygons
• Define: areas of high
occurrence versus areas
of low occurrence

17. Hot Spots
within 500’ of
Bus Stops
Optimized Hot Spot
Analysis
• Input: Points Inside 500’
• Count: Events inside
clipped polygons
• Shows higher
concentration
within 500’ bus stops

18. Kernel Density
vs
Hot Spot
Heat Map
Kernel Density Map
• Input: All Crime Points
• Each raster cell is
assigned a density value
• Entire layer is visualized
using a gradient

20. Null Hypothesis is False
There is a correlation between the location
of bus stops and criminal behavior.
Alternative Hypothesis is More True
The density of criminal
behavior is positively correlated with the
proximity to bus stops
CONCLUSION

21. 3x greater chance of
being victimized
or committing a crime
within 1000 feet of a
bus stop—than not.
WARNING: