1. Does Crime take the Metro?
Kyle Scholz - Public Policy M224A

2. Project Goal
Determine whether or not a mass transit system exports crime from high risk to low risk areas.

3. Method
Study the three years before and after the expansion of the Metro Red Line to Hollywood (in 1999/2000)
Use results to predict the effect of the Expo (Aqua) Line to Culver City

4. Skills: Inset map is shown
Skills: Inset map is shown. Attribute subset selections was used in isolating the red line expansion from the red/purple shapefile originally acquired.

5. Geoprocessing: used to clip & union reporting areas. Images: shown
Geoprocessing: used to clip & union reporting areas. Images: shown. Georeferencing: with no proper shapefile or coordinates for outdated LAPD reporting areas, georeferenced images found online and traced. Confirmed their usability by comparing areas calculated in ArcGIS to areas found in historical LAPD statistical reports.

6. Aggregate attribute fields: found average of three years type I offense data, normalized it by area. Create indices: used old scans of police data to create table of type I offenses by area, then joined it to the shapefile I created for the reporting areas of that time. Boundary subsets selections: used to find reporting areas containing red line extension stations.
*Type I Crimes include: Homicide, Rape, Aggravated Assault, Robbery, Burglary, Larceny, Vehicle Theft

7. Aggregated attribute fields to get % change
Aggregated attribute fields to get % change. Created indices listed on previous slide, Boundary subsets selections as listed on previous slide.

8. So what can we discern from this mixed result?
Crime Summary
One low crime area increased in crime
One low crime area decreased in crime
One high crime area increased in crime
One high crime area decreased in crime
So what can we discern from this mixed result?

9. Crime Analysis
If we ignore the anomalous Northeast area (because it has only one stop in its far corner)
We can see that the effect of the red line is the opposite of what the “crime exporting” theory predicted
The high crime origin of the line at Rampart dramatically increased in crime
The lower crime destinations (Hollywood and North Hollywood) actually decreased in crime

10. Possible Explanations
Coincidence
Very likely, but also very uninteresting for this project
Preference
Criminals may prefer above-ground light rail over Red line’s subway, for ease of entry/exit
Economics
Red line extension may allow lawful workers to commute out of the Rampart district and bring money home
If more money came into the Rampart district, criminals may have no need to ride the Metro to find victims
We can test this by seeing the results of the Red line on the local economy…..

11. Aggregated attribute fields to get % change
Aggregated attribute fields to get % change. Created indices listed on previous slide, Boundary subsets selections as listed on previous slide.

12. Aggregated attribute fields to get % change
Aggregated attribute fields to get % change. Created indices listed on previous slide, Boundary subsets selections as listed on previous slide.

13. Why is this so, and how can it explain the crime trend?
Income Summary
Lowest income area increased income
Upper income areas decreased income
Why is this so, and how can it explain the crime trend?

14. Income Analysis
The installation of the metro Red Line extension coincided with the beginning of a increase in median incomes of up to 50% in the high crime Rampart area
It also coincided with a decrease in median incomes across the lower crime Hollywood corridor
These could be a result of increased commuting by lawful workers from Rampart to Hollywood:
Rampart residents can bring wages home from Hollywood, increasing median income.
Hollywood residents must compete with new commuters, decreasing their median income.

15. Income vs Crime
Increasing the median income in the already-high crime Rampart area provides an added incentive for criminals to continue (or increase) the amount of crime there.

16. Skills: Inset map is shown
Skills: Inset map is shown. Attribute subset selections was used in isolating the red line expansion from the red/purple shapefile originally acquired.

17. Google API
To access:

18. Graduated symbols are shown on map
Graduated symbols are shown on map. Boundary subsets used to apply crime data to stations contained within them. Geoprocessing used to generate the background map of crime

19. Areal Weighted Average Model

20. Graduated symbols are shown on map
Graduated symbols are shown on map. Boundary subsets used to apply crime data to stations contained within them. Geoprocessing used to generate the background map of crime

21. Crime Predictions
If the pattern seen at the Red Line extension occurs at the Expo Line, we can expect that:
Crime will increase at the downtown (northeast) end of the Expo line, where crime is already the highest.
Crime will decrease at the Culver City (southwest) end of the Expo line, where crime is already the lowest.
CRIME
CRIME

22. Buffering used to select regions within 0. 5 miles of expo line
Buffering used to select regions within 0.5 miles of expo line. Geoprocessing used to clip census income data to highlight the nearby data.

23. Crime Predictions
If the pattern seen at the Red Line extension occurs at the Expo Line, we can expect that:
Income will decrease at the Culver City (southwest) end of the Expo line, where income is currently the highest.
Income will increase at the downtown (northeast) end of the Expo line, where income is currently the lowest.
INCOME
INCOME

24. Conclusion
The historical example of the Red line extension showed that the installation of a transit system can coincide with:
Income increasing conservatively
Poor areas increase in income, perhaps due to increased commuting
Rich areas decrease in income, perhaps due to competition for jobs with commuters
Crime increasing non-conservatively
High crime areas become even more violent
Low crime areas become even less violent
Possibly a result of the income trends above
If this pattern holds true for the Expo Line:
Culver City will have less crime, but lower incomes
Downtown will have more crime, but higher incomes

25. Questions?