1. Time in Hotspot
Brett Lord-Castillo
GIS Programmer
St Louis County Emergency Management
April 10th, 2013

2. A simple problem
 Given a set of designated crime “Hotspots”
 Find out how much time police vehicles spend in
those hotspots
 Which hotspots?
 Which days?
 What hours?
 Which cars?

3. The data
 Automatic Vehicle Location (AVL)
 Car ID
 Latitude/Longitude
 Timestamp
 Every 30 seconds per vehicle
 Hundreds of thousands of records per day

4. The data-complications
 No specific order
 Transmitters malfunction (and we lose a car)
 Receiver malfunctions (and we lose hours)
 5 minute stopped = stops transmitting
(But GPS Drift can bring it back on)
 Thirty seconds is rarely thirty seconds
 New dataset every day
(And sometimes we even lose a day)

5. Manual method
 Convert Latitude/Longitude to XY Point table
 Select by Location with Hotspots polygons
 Export and sum up number of returns
 Assume each return is 30 seconds
-or-
 Manually assign times to each point
 Sum up time on all returns

6. Why manual doesn’t work
 Very time consuming, especially with manually
assigned times
 Have to redo selections for each dimension
 By Hotspot
 By Car
 By Day of Week
 By Time of Day

7. The Workspace

8. Not as complicated as it looks

9. Initialize and collect records
with a blocking transformer

10. Inside the Loop: Three Date Formats
Day of the Week: String created by format %a (Name of day of week)
Hour of Day: Number created by format %H (24-hour hour of day)
epoch: Number created by format %s (seconds since epoch)
_totaltime: Placeholder to assign time for each GPS return

11. Get some more information
fme_feature_type: Keep track of which points are from this week
_prevcar: Car ID from the last feature processed
(We store this later)

12. Assign the time this return is worth

13. Set aside info for next feature

14. Spatial Filter
Select by Location, Spatial Join,
and Blocking Transformer all in one

15. Output: Save Our Work
(With fanout writer)
Week1019_1025 Pings1019_1025

16. Points for analysis
And one sheet in an Excel Workbook

17. Last two sheets in the workbook

18. Outcomes

19. Comparison
 First manual attempt took over 4 hours
 (To process one day)
 And assumed one point = 30 seconds
 Single stat (total time by hotspot)
 FME ran entire week in under 30 minutes
 Automated
 Less assumptions
 More dimensions (By Car, By Day, By Hour)

20. Thank You!
 Questions?
 For more information:
 Brett Lord-Castillo, blord-castillo@stlouisco.com
 St Louis County Emergency Management
 @blordcastillo
 https://github.com/marigolds6