South Jersey Rail

1. South Jersey Rail Past, Present and FutureJohn J ReiserSenior Seminar

2. The Future of South Jersey Rail • As the number of residents in the area increase, the need for effective, efficient mass transit will increase. • As gas prices increase, more residents will choose mass transit, provided it is close and can get them where they want to go. • The infrastructure is there: we need more stations.

3. Looking into the Future How exactly do we “guess” where stations should go? How do we know if stations will be effective? • Find out how accessible stations are. • Find out how many stations are needed.

4. Methodology In Gloucester County, there’s an existing rail line that runs from Camden to Millville. Are there a significant number of county residents that live within walkable distance to a rail station? Using GIS, we can calculate the number of residents within various distances of the rail line.

5. Data Needed Parcels Rail Line Roads Land Use

6. Finding Housing Points We start with an intersection function, which produces a new polygon where there are two polygons that intersect. By intersecting the parcel data with the residential values in the land use data, we create new polygons that represent areas that are developed with residential housing units. intersects

7. The Intersection The new layer is where parcels and residential land use intersect.

8. Slivers Sliver Polygons Sliver polygons occur when there is a mismatch between the two intersected layers. These small slivers negatively impact the calculation by falsely increasing the amount of housing points we will generate.

9. Removing the Slivers Considering the slivers are usually long, small, and thin, we can assume that... • They will be relatively small. • They will have a disproportionate ratio of perimeter to area. Removing all the polygons from our layer that are less than 1/10th of an acre and have a perimeter/area ratio of greater than .3 takes care of those nasty sliver polygons.

10. Finding the Housing Points By calculating the centroid, or center point of a polygon, we can use the centroids of our intersected layer to estimate the most likely location of a house.

11. Finding the Housing Points But, do they line up with actual houses?

12. Housing Points and Aerial Photos Looks like it to me! But we should make sure.

13. Normalizing the Data All of our data is for the year 2000. The aerial photos are from 2002. There will be new houses on the aerials that won’t have dots, so besides being incredibly time consuming, verifying housing points against the aerials wouldn’t be possible. The US Census has a wealth of information on population and housing...

14. Normalizing the Data Taking the Census housing data, adding the number of points to each Census Block, the smallest area measured by the Census, we can compare the number of houses generated to the number the Census counted.

15. Normalizing the Data Each block now has a point count Housing Points Census Blocks

16. Normalizing the Data The houses aren’t exactly where they should be all the time, and because there is a chance of having too many points due to sliver polygons, we normalize the data against the Census to get a population value for each dot. The population value will help us get a more accurate value for the amount of people that live near the rail line.

17. Housing Points and Distance We now have a set of accurate housing points, but we’re nowhere near done. In GIS, it’s easy to calculate the straight line distance from one point to any other given point... but how often do you travel in a straight line when you go to work? There’s rarely a time when we can walk/bike/drive a straight line to our destination.

18. The Road Network Most often, you will travel along a road network, regardless if you are walking, biking, or driving. (Sidewalks are there for a reason.) Using the GloucesterCounty road network,we can calculate the distance by road to everyhouse in the county.

19. Where to? The software needs to know of a destination that we’re calculating for our road distance. When we define the distance, the GIS will give each segment of our road network the a value that is the distance on the road network to the closest destination. What’s our destination? The train stations!

20. RiverLine “South Corridor” Gloucester County Light Rail Looks familiar?This is the original plan for the RiverLine, which opened this past March. The difference? The new line stops at Camden. Gloucester County Times,26 Jan 1997

21. The Railroad Stations To set the South Corridor stations as destinations, we will add points on our road network where road and rail cross that are closest to the proposed stations. Now, we let the computer calculate the distance from the stations to every point on the road network.

22. Distance by Road Network The computer analyzes the distance from each station to each point on the road network. Yellow is within walking distance, purples are within biking distance, and blue areas are more than 3 miles away.

23. Power to the People! We have housing points, and a measure of distance from each station along the road network. It’s time to put the two together and see how many people will have car-free access to the Gloucester County Light Rail line.

24. Allocation of the Road Network Our housing points are not on the road network, they’re set back off the road. In order for us to calculate the distances from the stations to the houses, we have to give the houses driveways. We do this using an allocation function.

25. Allocation of the Road Network The allocation fills in the gaps between the road and the housing point, but the value is just that of the road network distance. The distance of the driveway is not included.

26. Driveway Distance A straight line distance layer is created, where each cell has a value that is its distance in feet from the closest road. Adding the straight line distance layer to the allocation layer creates a surface where each point has a value that is the distance to the closest station by going straight to the road network, then using the road to get to the station.

27. Let’s look at that Countywide.

28. Countywide Analysis Distance on Road Network Allocation Function Straight Line Distance Addition of Layers Housing Points

29. Applying Our Findings

30. The Controversy • Some people believe that “the criminal element” will ride trains down from Camden and commit illicit acts in their neighborhoods. • Some people believe that the rail line will crush their children. • Light rail is safer than the freight that currently runs on the line approximately three times a day.

31. The Route 55 Option • Route 55 was designed so that the grass median could be used as a rail right of way if needed. • Many citizens that fought restoring passenger service on the existing line (for various reasons) cited Route 55 as a better alternative to rail transit in Gloucester County.

32. Social Engineering or Common Sense?

33. “Fighting the Good Fight™”

34. Are trains killers? Steve Graham sites the following as why restoring the existing line as a “bad thing” • Safety • Ridership numbers • Cost to taxpayers • Influx of crime • Parking in small towns • Quality of life He doesn’t cite anything to back himself up!

35. The Existing Rail Percent of Total Homes15.81 are within 1mi43.38 are within 3mi Route 55 Corridor Percent of Total Homes 1.87 are within 1mi25.66 are within 3mi The Numbers – Housing Units

36. The Existing Rail Percent of Population18.27 are within 1mi44.91 are within 3mi Route 55 Corridor Percent of Population 1.51 are within 1mi26.04 are within 3mi The Numbers - Population

37. Guess Who? 0.35mi from Conrail1.64mi from Route 55 3.37mi from Conrail1.75mi from Route 55 5.07mi from Conrail4.61mi from Route 55 0.83mi from Conrail2.42mi from Route 55