Jay Monty
11/24/10
GIS Assignment 7
Assessing Opportunities for Rail Transit Expansion .
Project Description:
The intent of this project is to identify locations in eastern Massachusetts which could
potentially support a new commuter rail station on either an existing commuter rail line or along
one of the several currently abandoned rail lines in the area.
I am choosing rail stations as opposed to rapid transit and bus stations. Most of the study
area lies a considerable distance from Boston. Commuter/regional rail is the most viable means
of public transportation to cover this range of distances. I intend to create a map showing the
locations of active rail lines as well as those which are out of service or abandoned. From
literature sources, I have determined the demographic criteria which are used to determine
whether a transit station can be supported by the local populace. These criteria include:
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High population densities covering an area equal to the “catchment area” of a commuter
rail station.
Proximity to a major urban center.
Proximity to another transit station.
Proximity to major roadways
Average household income.
Educational attainment.
Housing value
Plus location along active or inactive railroad line?
While patrons of commuter rail often fit certain patterns relating to household income,
educational attainment, and housing value, I have decided not to include these three criteria in
my analysis. To do so would in fact suggest that commuter rail should only be brought to
relatively affluent communities, when in fact these are the communities that may need it least.
Finally, I will rank census blocks based on the how well they meet each of the remaining criteria.
The intended outcome, if these criteria are ranked appropriately will be the identification of
potentially viable commuter rail stations.
Methodology:
I will first isolate eastern Massachusetts by isolating those counties inclusive and east of Worcester
County. The criteria listed above is primarily census and infrastructure data which is available through
MassGIS. I will base the analysis on census blocks and apply data on population, income, housing value,
etc. to the census blocks. I will use a combination of selections by attribute to isolate “transit friendly”
areas. I will then use selections by location to determine which of these areas are physically located near
an active or inactive rail line.
Data and GIS Layers:
Data Layer
File Name
Census Blocks
CENSUS2000BLOCKS_POLY.shp
Assorted Demographic Data
CEN2K_BG_LEGATTRIB.dbf
Major Roads
EOTMAJROADS_RTE_MAJOR.shp
MBTA Stations
MBTA_NODE.shp
Railroad Lines
TRAINS_RTE_TRAIN.shp
MBTA Transit Lines
TRANSLINES_ARC.shp
Accuracy (feet)
50
50
50
50
Steps:
1. Selection of census blocks by population density and access to existing infrastructure.
a. Select out Massachusetts counties which are inclusive and east of Worcester County.
This comprises what is typically referred to as eastern Massachusetts.
b. Select, using the “select by attribute” tool, census blocks with relatively high population
densities. (Commuter rail typically requires a minimum density of 2 dwelling units per
acre)
c. Select, by location, census blocks which are within a 1.5 mile radius of an existing
railroad line or abandoned rail bed. This identifies the general catchment areas of the rail
line.
d. Select, by location, those census blocks which are not within 3 miles of an existing
MBTA station. This prevents duplicating existing stations.
Note: The use of distances will be “as the crow flies” and not network distances. The
reason for this is that people access the commuter rail both by foot and by car. The
network distance would in fact be useful particularly for foot travelers who are more
sensitive to small changes in walking distance. However, since the catchment area set for
passengers with private vehicles, they are more affected by travel time rather than
distance, which is not well represented in a network analysis (particularly in urban areas)
unless there are major geographic obstructions to the street system. This is probably not
the case in most areas of eastern Mass.
2. Reclassify the data sets so that a ranking scheme can be created. Part one selected some
general attributes which will give the “catchment areas” for potential stations; that is, the
areas that will provide the bulk of the passenger base. This next portion will rank census
blocks within those catchment areas that may be the best location for a station.
a. Reclassify population density on a scale of 1 through 5. Since we have already
selected census blocks with a minimum density of 2 dwelling units per acre, this will
rank as 1, with increasing densities ranking higher.
b. Reclassify census blocks as to whether or not they intersect a railroad line (stations
need to be along an existing railroad or ROW). This is a binary classification. A zero
would indicate no intersection, a 1 would indicate a railroad running through the
block.
c. Reclassify census blocks by distance from a major road.
3. Create a weighting system using the Raster Calculator.
The weighting system will be somewhat complex. The most obvious system of ranking
blocks by density and proximity to a railroad is not necessarily ideal. Some
considerations are:
While population density is important, it is also important for the census block containing
the proposed train station to be adjacent to other census blocks with high density. The
ideal location for a train station may be an area that has some vacant land immediately
adjacent (thus lowering the overall density of the block) but is surrounded by other blocks
which have very high densities. Thus a higher ranking will need to be given based on
surrounding densities, not just density of the individual block.
Distance from major roads is important. It may be desirable to have a station in very
close proximity to a major road and construct a park-and-ride facility. However, places
without access to a major road are also desirable if we want to improve access to
underserved areas. Thus, blocks either very close or very far from a major road will get a
high ranking relative to a block that is a moderate distance from a major road.
The final product will be a map showing overall rankings of census blocks in relation to how well suited
they are to hosting a new commuter rail station. Visually, it will show groupings of census blocks which
will represent the catchment areas for a new station. Within each catchment area, a single block will be
highlighted as a proposed location for a commuter rail station
This map will be supported by several secondary maps showing rankings based on various types of
infrastructure and population density. One map will show existing commuter rail lines and existing active
railroad lines. Another may show where extensions of the existing system would be feasible based on the
analysis. A third map may show areas of high density which do not have access to rail transit service.
Sources:
Matisziw, Timothy C.; Murray, Alan T.; Changjoo, Kim. 2006. Strategic Route Extension in Transit
Networks. European Journal of Operations Research. 171 (2). June 2006. pp. 661-673
-This article discusses exactly the type of GIS analysis I wish to perform for this project, albeit on
a more detailed level than what is required for this project. It discusses how spatial analysis can
be used to find optimal routes for new transit services and stations.
Cervero, Robert. 2007. Transit-oriented development’s ridership bonus: a product of self-selection and
public policies. Environment and Planning 39, pp. 2068-2085.
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This article discusses transit oriented development and the “catchment area” of transit stations. It
discusses how physical attributes of a neighborhood or development influence a person’s decision
to use transit.
McGuckin, Nacy A.; Srinivasan, Nanda; 2003. Journey to Work in the United States and its Major
Metropolitan Areas – 1960-2000. U.S. Department of Transportation.
-This lengthy report details the commuting characteristics of several dozen major US cities
including data on transit availability and ridership.
Urban Transportation Planning, 2nd Edition. Michael Meyer and Eric Miller. McGraw-Hill, New York,
2001.
This is a text book used by several transportation planning courses. For the purposes of this
project, it provides hard data on what population densities are required to support different modes of
transit.