UNDERGRADUATE THESIS
The Implications of Improved Access to Public Transportation: The Green Line Extension
11.ThU | May 21, 2009 Student Name: Margot Spiller Thesis Advisor: Professor Joseph Ferreira
2 Table of Contents
INTRODUCTION 5 Background 5 Purpose of this Thesis 8
LITERATURE REVIEW 10 Transit Development Theories 10 Defining and Measuring Access 13 Impacts of Transit Stations on Surrounding Neighborhoods 14
RESEARCH QUESTION 19
METHODOLOGY 21 Choosing the Station 21 Collecting the Data 22 Application to the Green Line Extension 23 Evaluating the Analysis 23
RESULTS 24 The Green Line Extension in Context 24 Variables Used to Evaluate Station Areas 25 The Existing Conditions of the Green Line Extension Station Areas 26 Comparison of the Green Line Extension to an Existing Station 30 Results of Davis Square Analysis 33
DISCUSSION 48 Discussion of the Davis Square Analysis Results 48 Application to the Green Line Extension 52
CONCLUSIONS 56
BIBLIOGRAPHY 58
APPENDIX 60
LIST OF TABLES Table 1 – Travel Impacts of Land Use Design Features 15 Table 2 – Census Variables Used to Test for Gentrification 16 Table 3 – Census Variables Used to Track Transit Impacts 26 Table 4 – Population Density of Green Line Extension Station Areas 28 Table 5 – Socioeconomic Characteristics of Green Line Extension Station Areas 29 Table 6 – Travel Behavior of Green Line Extension Station Areas 30 Table 7 – Characteristics of the Davis Square Area in 1980 32 Table 8 – Population Density from 1980-2000 for Davis Square and Control Areas 35
3 Table 9 – Percentage of Vacant Housing Units from 1980-2000 for Davis Square and Control Areas 36 Table 10 – Median Non-Condo Housing Value from 1980-2000 for Davis Square and Control Areas 37 Table 11 – Median Rent from 1980-2000 for Davis Square and Control Areas 38 Table 12 – Unemployment Rate from 1980-2000 for Davis Square and Control Areas 39 Table 13 – Workers with White Collar Jobs from 1980-2000 for Davis Square and Control Areas 40 Table 14 – College Graduates from 1980-2000 for Davis Square and Control Areas 41 Table 15 – Median Household Income from 1980-2000 for Davis Square and Control Areas 42 Table 16 – Median Family Income from 1980-2000 for Davis Square and Control Areas 43 Table 17 – Percentage of Commutes via Automobile from 1980-2000 for Davis Square and Control Areas 44 Table 18 – Percentage of Commutes via Public Transportation from 1980-2000 for Davis Square and Control Areas 45 Table 19 – Percentage of Commutes Longer than 30 Minutes from 1980-2000 for Davis Square and Control Areas 46
LIST OF FIGURES Figure 1 – Distance Criterion for Public Transport Access 14 Figure 2 – Transit Proximity Impacts on Travel Behavior 15 Figure 3 – Inner Core Towns and Existing Transit Services 25 Figure 4 – Proposed Green Line Extension Stations Accessible by Somerville 26 Figure 5 – Land Use Categories of Somerville Parcels for 2005 28 Figure 6 – Land Use of Somerville in 1971 32 Figure 7 – Population Density from 1980-2000 for Davis Square and Control Areas 35 Figure 8 – Percentage of Vacant Housing Units from 1980-2000 for Davis Square and Control Areas 36 Figure 9 – Median Non-Condo Housing Value from 1980-2000 for Davis Square and Control Areas 37 Figure 10 – Median Rent from 1980-2000 for Davis Square and Control Areas 38 Figure 11 – Unemployment Rate from 1980-2000 for Davis Square and Control Areas 39 Figure 12 – Workers with White Collar Jobs from 1980-2000 for Davis Square and Control Areas 40 Figure 13 – College Graduates from 1980-2000 for Davis Square and Control Areas 41 Figure 14 – Median Household Income from 1980-2000 for Davis Square and Control Areas 42 Figure 15 – Median Household Income from 1980-2000 for Davis Square and Control Areas 43 Figure 16 – Percentage of Commutes via Automobile from 1980-2000 for Davis Square and Control Areas 44 Figure 17 – Percentage of Commutes via Public Transportation from 1980-2000 for Davis Square and Control Areas 45 Figure 18 – Percentage of Commutes Longer than 30 Minutes from 1980-2000 for Davis Square and Control Areas 46
4 Introduction
Background
Densely populated metropolitan areas present unique challenges to urban planners in terms of economic development, land use patterns and transportation infrastructure, among other considerations.
The Metropolitan Area Planning Council has defined an “Inner Core” region of twenty cities and towns in the Boston area that exhibit these characteristics because of their urban and populous nature. Among these communities is the town of Somerville, which is the target of a proposed transit infrastructure extension.
Somerville is located in Middlesex County, Massachusetts, two miles north of Boston. With
77,000 residents in 4.1 square miles, Somerville is the densest city in New England. Almost one third of the population is foreign born, and certain areas of the town have high concentrations of moderate and low-income residents. As of the 2000 census, the median income for a household in the city is $46,315, and the median income for a family is $51,243 (U.S. Census Bureau 2000). Twelve and one-half percent of the population and 8.4 percent of families are below the poverty line, and out of the total population,
14.3 percent of those under the age of 18 and 13.6 percent of those 65 and older are living in poverty.
Furthermore, more than one fourth of the town’s households do not own a car (STEP 2008). Because of these factors related to median income and minority populations, much of Somerville has been designated by the State as environmental justice population areas 1. Environmental justice regulations are in place to ensure that the programs and activities of the Federal government do not disproportionately affect the human health or environment for minority and low-income populations in the United States.
1 Executive Order 12898, “Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations”, requires that each Federal agency shall, to the greatest extent practicable and permitted by law, “make achieving environmental justice part of its mission by identifying and addressing, as appropriate, disproportionately high and adverse human health or environmental effects of its programs, policies, and activities on minority populations and low-income populations” (Center for Environmental Excellence).
5 Despite these considerations, the majority of Somerville does not have adequate access to public transportation. With only one transit station in Davis Square, many residents resort to buses and automobiles to reach their destinations. This constrains the already congested roadway network, leading to unreasonably long travel times for the relatively short distances of many trips within the Inner Core
(Vanasse Hangen Brustlin (VHB), 2-2). Bus service is further hindered by overcrowding, unreliability, and the fact that transit patrons often have to make multiple connections to reach their destinations. These factors lead to inadequate access to Boston and other destinations, hampering economic development and employment opportunities.
Beyond inadequate access, Somerville has suffered major environmental impacts from the 46-acre
MBTA Commuter Rail Facility located in its boundaries, as well as the infrastructure of I-93, Route 28 and other major arterials that bring with them large volumes of regional traffic. Somerville is located in an area designated non-attainment for ozone by the U.S. Environmental Protection Agency (EPA), with a classification of “serious” (VHB 2-3). The leading sources of ozone precursor emissions within the area are motor vehicles. The community’s concern of air pollution is furthered by the area’s increased rates of chronic diseases such as cancer death, asthma and obstructive pulmonary diseases.
In the early 1990’s, the Commonwealth of Massachusetts committed to implementing a number of
Boston region transit improvements as mitigation measures for the Central Artery/Tunnel Project. This commitment was embedded in the State Implementation Plan to ensure air quality conformity. Among the proposed improvements was an extension of the Green Line through Somerville and Medford (Green Line
Extension 2008). The Green Line Extension would have multiple stations within or within walking distance of Somerville, including Union Square, Washington Street, Gilman Square, Lowell Street, Ball
Square and College Avenue.
6 The goals of the extension are to improve mobility and regional access for residents in Cambridge,
Somerville and Medford. Improved mobility in the area will allow residents to more easily travel through the study area and to downtown Boston (VHB 2-4). In turn, residents would benefit from greater employment access and reduced commuting times. The Extension also plans to improve the efficiency and effectiveness of the transportation system by expanding the viability of multiple mode choice options.
Residents will benefit from multimodal connections between commuter rail, bus services and light rail that will improve mobility and flexibility in route choice.
By improving access and mobility, the project also aims to improve air quality and minimize environmental impacts. Mobility improvements will help to move the area towards compliance with
National Ambient Air Quality Standards, as well as improve the overall environmental conditions in the study area.
Advocates of the extension believe that train service is a crucial component to the city’s future economic viability, as it will help businesses grow and bridge critical tax dollars for the city to pay for needed services. Often cited is the transformation that has occurred in Davis Square, an area of
Somerville that changed dramatically after the Red Line was extended into Davis Square in 1984.
Beginning in the 1950s, the area fell into decline, and by the early 1970s the area was characterized by empty storefronts and deteriorating buildings and infrastructure (MassGov). Today,
Davis Square is known as a vibrant urban center that boasts a mix of retail, office, institutional, residential and entertainment uses. The City successfully integrated redevelopment of existing structures with new development of over 170,000 square feet of office and retail space, as well as new multi-family housing, making it a model for transit-oriented development. Many believe that similar changes can occur in
Union Square and other proposed transit station locations in Somerville once the Extension is completed.
7 Purpose of the Thesis
The City of Somerville has long advocated for increased public transportation routes within its boundaries, as the City believes that increased access to public transportation will improve economic, environmental and social conditions of the area for its residents. To justify the public funds of such a project, it is important to have an accurate idea of the impacts on Somerville by the implementation of the
Green Line Extension, not only in terms of access, but of changes in land use, population characteristics and other factors. While the Davis Square area may have had increased economic potential after the station was implemented, what other effects did the transit line have on the nearby residents? Having an accurate and complete picture of the repercussions of public transportation service on the surrounding community is crucial so that the potential undesirable impacts can be addressed.
While there are a number of questions to ask of the Green Line Extension’s effects on Somerville, the intention of this thesis is to quantify the likely changes in access resulting from the proposed Extension and, using these results, determine the possible implications that increased access may have on surrounding populations. Establishing which areas will have newly-acquired access to transit services will provide an accurate picture of the existing population in terms of land use, socioeconomic characteristics and travel behavior. These existing characteristics will be used to predict the potential changes that the
Green Line Extension will have on the community.
While predicting the effects of a publicly funded project is worthwhile, the data and technology to do so has not been available to non-professionals until recently. Census data, which is now largely available online and through library resources, provides a wide array of information about population characteristics throughout the past forty years. Furthermore, within the past decade, Geographic
Information Systems (GIS) has provided an accessible means for analyzing this data. This thesis, then, will investigate the extent to which these technologies can be used to study the impacts of public
8 transportation projects. The results of this investigation will establish what analyses can be done using commonly available resources and what should still be left to professional analysis.
9 Literature Review
The literature review is broken up into four sections. The first section discusses the existing theories about the effects of transit on surrounding communities, transit-oriented development and the debate over compact development versus sprawl. The second section discusses both the definition of access with respect to transportation and the various methods traditionally used to measure an accessible level of transit. The third section reviews the observed implications of transit stations on the surrounding neighborhood, and the fourth discusses the expected impacts of the proposed Green Line Extension on the residents of Somerville.
Transit Development Theories
There are several popular theories in the planning world regarding the potential effects of locating a transit station in a neighborhood. First, location theory will be reviewed, which addresses the effect of transit accessibility on the cost of movement, in terms of money and/or time. Secondly, the degree to which urban form can affect the realizing of transit benefits will be discussed by reviewing transit-related development and transit-oriented development. Finally, the debate between light rail and bus rapid transit will be reviewed.
Location Theory
The basic concept underlying the land-use and transportation relationship is accessibility.
According to Giuliano (1986), as movement becomes less costly (in terms of money and/or time), accessibility increases. The introduction of a rail line leads to greater accessibility for the area lying within the transit corridor, giving it a relative advantage over those areas not served by the line. With all else being equal, activities will shift towards those places that have become more accessible.
Traditional location theory, as devised by Alonso (1964), assumes a monocentric city where
10 employment is in the central business district (CBD). As such, commuting prices increase with distance from the CBD. In exchange for the lower commuting costs associated with being located near the center, an individual is willing to pay higher rents. Following this theory, rents will be the highest at the center where transportation costs are lowest.
As a result of these land value increases, accessible areas will see greater development densities
(Huang 2002). If land value is a factor in the production of a good or service, then its price will be higher and it will be used proportionally less than other factors. It follows that land will be used more intensively to account for its higher per-unit cost.
Location theory suggests that accessibility to activity centers will determine where an individual or business chooses to reside (Giuliano 1986). An individual will live at the location at which the marginal savings in rent from living further from the CBD equals the marginal cost of commuting. Similarly, businesses locate in the area that maximizes accessibility to employees, clients and customers or best facilitates the shipment of product inputs and outputs. From these guidelines, the theory predicts that the
CBD will be the most intensely developed area.
With these principles in mind, location theory must be used in the context of the modern transportation network. In most urban areas, new rail lines will only marginally improve the accessibility to the region, since there is already a vast network of streets and highways (Huang 2002). The effects that a new transit line will have on regional development will be marginal; instead, it will redistribute development that would take place elsewhere in the region to the immediate vicinity of the station.
The Urban Form and Transportation Connection
The extent to which constructing a transit line will affect the surrounding neighborhood’s characteristics in terms of land use, travel behavior and socioeconomic factors depends largely on the type of development around the station. Planners have long advocated for transit-oriented development (TOD)
11 as a way to reverse the urban sprawl development patterns that have dominated growth throughout the 21st century in the United States, which are seen as unsustainable and inequitable. TOD focuses on compact, walkable communities centered around public transportation systems, with the goal of achieving a higher quality life without dependence on a car for mobility and survival. Key components of TOD include a walkable community design, a prominent train station in the town center, mixed land use, high density development and reduced parking in the town center (Center for Transit Oriented Development).
Unfortunately, many past attempts at maximizing transit benefits to the community have not lived up to expectations. Belzer and Autler (2002) term these past development attempts as transit-related development, which narrowly defines the relationship between transit and development. Transit-related development arises when transit agencies and the federal government seek to capture the value created by rail systems by creating large-scale real estate developments on transit agency owned property. Instead of maximizing the community benefits of the system and focusing on how transit should be integrated with the larger area, this type of development focuses on the maximization of financial benefits for the parties involved. Because of this decision to focus on revenue-maximizing real estate, these projects have not experienced the transit ridership increases promoted by TOD advocates.
Light Rail versus Bus Rapid Transit
When designing a transit system to maximize the benefit-cost ratio of the investment, there are differing opinions about whether light rail or bus rapid transit (BRT) is the best approach. In terms of cost, the capital costs of a BRT system are generally lower than light rail capital costs when compared on a cost-per-mile basis, and the operating cost differences of the two are not conclusive (GAO 2001). With respect to performance, the two systems have also shown to have similar ridership and operating speeds.
Beyond cost and performance measures, BRT and Light Rail each have a variety of advantages and disadvantages. BRT generally has the advantage of (1) having more flexibility than light rail, (2)
12 having the ability to phase in service rather than having to wait for an entire system to be built, and
(3) being used as an interim system until light rail is constructed. According to transit operators with experience in BRT, one of the challenges faced by BRT is the negative stigma that potential riders attach to buses regarding their noise, pollution, and quality of ride. Light rail has advantages, according to transit officials, associated with increased economic development and improved community image. On the negative side, building a light rail system can have a tendency to provide a bias toward building additional rail lines in the future.
As shown above, both BRT and light rail are compelling options for a transit project.
Choosing which system is more appropriate has to be made on a case-by-case basis considering multiple factors such as cost, ridership, environmental impacts and community needs (GAO 2001).
Defining and Measuring Access
In developing a public transportation system, the interrelated issues of access and accessibility should be addressed. Access is the opportunity for system use based upon proximity to the service and its cost (Murray 1998). If distances or barriers to access a service are too great at the origin or destination of a trip, the service is not likely to be the utilized as a mode of travel. Similarly, if the cost is too expensive because there are cheaper services, the service is also not likely to be utilized.
Accessibility in the transportation field is defined as the ability of the public transport system to allow individuals to reach desired goods, services, activities and destinations in a reasonable amount of time (Litman 2008, Murray 1998). Access and accessibility are related through the fact that access to transit allows for greater service accessibility, since the time needed to reach a transit service affects the overall ability of an individual to reach a desired location through that transit service. With these definitions, the distinction between access and accessibility of the public transport system is clear. While
13 both access and accessibility are both important for a successful and well-utilized public transport system, this thesis will focus on access through proximity to services.
Ensuring service coverage to public transport services is an important point since the time needed to reach a public transport station or stop has a significant impact on total travel time, which affects ridership (Murray 1998). Pedestrians are most likely to use transit services if the beginning and end of their trip is close to a transit facility. As a general rule, 400 meters represents the distance of a comfortable walk for most people under normal conditions (Calgary Transit Division 2006). Therefore, residents who can reach a transit facility within this distance have adequate access to public transportation.
Figure 1 – Distance Criterion for Public Transport Access (CTD 2006)
Impacts of Transit Stations on Surrounding Neighborhoods
Vehicle Miles Traveled
Proximity to transit stations has also been shown to decrease vehicle miles traveled in households.
Research by the San Francisco Bay area Metropolitan Transportation Commission indicates that households living near rail and ferry terminals drive significantly less and rely significantly more on public transit than households further from transit. Arrington, et al. (2008), found that Transit-Oriented
Developments generate much less (about half) of the automobile trips as conventional, automobile- oriented development.
14 Looking at the reduced vehicle trip generation rates for various development schemes around the station can further break down the impact of rail stations on vehicle miles traveled. Table 1 below illustrates that the reduction in vehicle miles traveled can span from five to twenty percent depending on the development in the area (Dagang 1995).
Figure 2 – Transit Proximity Impacts on Travel Behavior (MTC 2006)
Table 1 – Travel Impacts of Land Use Design Features (Dagang 1995)
Gentrification
While there are many positive outcomes linked to locating a transit station in a neighborhood, including higher transit ridership, new business, and added tax revenues, some critics have suggested that transit-oriented development (TOD) can lead to gentrification. Jeffrey Lin, in “Gentrification and Transit
15 in Northwestern Chicago” (2002), found that “the presence of transit, in combination with declining automobile costs, leads to gentrification of inner-city, transit-served neighborhoods” (Lin 2002, 175).
Lin stated that gentrification can be measured in two ways, including the measurement of changes in housing market activity, such as price changes, renovations permits and sales, or changes in household status, such as household size, structure, income and education. Using only the measurement of housing market activity, Lin concluded that a premium in land value closer to transit stations results in gentrification. “The key variable, distance to transit, had a significant and strong negative effect on property value change… This finding is consistent with the hypothesis that transit was a spur to gentrification,” (p. 184).
While Lin relied on housing market activity to measure gentrification, other scholars have used a variety of census variables to measure changes in household status. Hammel and Wyly (1996) created a model using the census variables, shown in Table 2 below, to test for gentrification using socioeconomic status, housing and total population variables.
Table 2 – Census Variables Used to Test for Gentrification
16 Residential Property Values
Many transportation studies have investigated the effect of rail transit stations on surrounding property values (Cervero et al. 2001, Diaz 1999, Lin 2002). There are four factors identified which may account for changes in property values – two which may increase property values around transit stations and two which may decrease values (Bowes et al. 2001). The first factor that may increase property values around rail stations is the access advantage provided by the rail station. Commuters will be willing to pay for properties close to rail stations if the rail offers a better transportation alternative to driving in terms of reduced commuting time or less tangible benefits such as a less hectic commute. The second positive factor is the neighborhood commercial services, such as retail establishments, that may move into the area. These additional services may benefit nearby residents regardless of whether or not they use the rail service, even though they may be primarily meant to service customers coming through the transit station.
Countering these factors are the negative externality effects of the station, including noise or pollution, as well as the potential increased crime rates due to the improved access to the neighborhood provided to outsiders (Bowes et al. 2001, Debrezion et al. 2007) . The overall impact on property values due to rail station proximity is based on the relative impacts of these positive and negative factors.
Other Effects
Research has shown correlations between proximity to a transit station to impacts in land use and population density. According to the Rappaport Institute, which looked into the impacts of Commuter
Rail service on the Greater Boston area, areas that gained commuter rail stations saw a higher-than- average increase in medium-density housing and commercial buildings between the years of 1971 and
1999 (Beaton 2006).
17 With respect to population density, the same report by the Rappaport Institute found that, through the 1990s, areas near active commuter rail stations generally saw slightly greater increases in population density than the region as a whole. The study also found that the densest areas were most likely to have a higher share of people using transit to get to work, which is corroborated in transit-oriented development theories linking transit use to high population densities (Dunphy et al. 1996).
18 Research Question
As shown by the literature review, the construction of a transit line using public funds is a debated topic. The use of public funds is approved by policymakers and accepted by the public under the assumption that the transit line will generate a number of benefits for the immediate surrounding area and the region as a whole. These benefits, generated by the increased accessibility to and from the area around the station, include decreased travel times and costs, increased land value and employment benefits.
With these considerations in mind, the purpose of this thesis is to explore the extent to which these benefits can be measured using available data and technology, using the proposed Green Line Extension as an example. Because the transit benefits are a product of the increased accessibility to and from the region, this question will be answered in a two-step process:
• How will residents’ access to public transportation change with the Green Line Extension in Somerville?
• What are the likely implications of increased access to public transportation for residents near the proposed transit stations?
In order to accurately answer these questions, there are several other factors that must be addressed. First, how can you measure the benefits of a project that hasn’t yet been implemented? Although a myriad of data is available for the past forty years, there is no data that tells how the community will change in the future. Therefore, determining the potential benefits of this project is not simply compiling information, but instead a puzzle to be put together and projected into the future. Secondly, given the available data and technology, what are the appropriate variables and tools to measure both the improved access and the subsequent benefits? Choosing the inappropriate variable or manipulating the correct variables in the wrong way both have the potential to yield inaccurate results.
After the implications of the Green Line Extension are estimated, this thesis will also aim to separate out the intended outcomes, such as better access to public transportation, from the unintended
19 outcomes, such as increased housing prices. Finally, a question which will be briefly touched upon, but is important to keep in mind throughout this thesis: Which of these factors are desirable, and to whom?
20 Methodology
Because the Green Line Extension has not yet been implemented, it is not possible to do a direct analysis on the impacts the system has on the surrounding areas. Instead, to predict these effects, the proposed stations will be compared to a similar recently implemented station.
Choosing the Station
In order for the results of an analysis on a different station to be projected onto the proposed Green
Line stations, the transit lines that connect to the stations in each project should have a similar level of service, and the initial population and land use characteristics of the stations’ surrounding areas should be comparable.
The level of service of the transit system is important because it will influence the degree to which accessibility changes, and hence the degree to which the community benefits from the infrastructure. A heavy rail line, which requires a much larger capital investment and has a higher level of service than, say, a bus line, will allow residents living or working around the area to reach more destinations. A heavy rail will also allow more travelers from outside the community to reach the area by transit, thus allowing for more economic benefits to the immediate vicinity. Because the level of service has a direct impact on the accessibility improvements to the area, comparing transit lines with different service levels will not yield the most accurate results.
In addition to level of service, the comparison station should have similar initial population and land use characteristics as the proposed stations. If an area around a station already has mixed land use or a relatively high population density, then one would not expect as great an impact on these variables as would occur in a single use or low density area. Similarly, an area whose population has a median income below the regional average would likely see a higher shift in socioeconomic variables than an area with residents that are already well off. Therefore, in order to have the results of the comparison be
21 transferable with respect to land use and socioeconomic factors, the conditions before the station was implemented should be similar to the existing conditions around the proposed Green Line Extension stations.
Collecting the Data
As mentioned in the research question, this thesis aims to analyze the effects of transit using commonly available data and tools. More specifically, the characteristics of the area surrounding the already-implemented station will be tracked using time-series census data and analyzed using GIS. The data will be collected for years both before and after the station was implemented so that the effect of the station can be easily determined. In order to get a complete picture of how the neighborhood has changed, the data collected should include these elements:
• Travel Behavior – The purpose of the transit line is to increase accessibility, which should affect the travel behavior of the surrounding population. By tracking variables such as commute time and travel mode, the magnitude of the transit’s effect can be determined.
• Land Use – The population density and commercial density of the area is of interest, since theory suggests that activities will cluster around the station.
• Socioeconomic Trends – Because the addition of a transit station is expected to increase the land values in the immediate vicinity, the median rents and housing values in the area should be monitored. Furthermore, because these increased values may potentially change the demographics of the population, the socioeconomic status of the residents is also of interest.
To effectively separate the effects of increased accessibility from general economic trends, this data must be compared to a control area that has not had an increase in accessibility during the time period at hand. The first control that should be used is a regional average for the variables being analyzed. In order for this average to give an accurate picture of the general trends that would be occurring in the analysis area, the region should be confined enough to only include areas with similar environments as the one being studied, but large enough to have a sufficient number of data points. Beyond the regional
22 average, a second type of control should be used that looks at an area with well-established transit services. This will ensure that there is not a trend occurring in all areas with transit access that is different from the metropolitan average.
Application to the Green Line Extension
Once the analysis on the existing transit station has been completed, the results can be projected on to the areas surrounding the Green Line Extension. Under the assumption that the two transit lines are comparable, the effects of the implemented line should be similar to the effects of the proposed line.
Therefore, a general estimate of the effects of the proposed line on the surrounding communities can be given. If certain stations within the extension differ from the compared station in terms of land use or existing population, the results will be modified to account for these differences.
Evaluating the Analysis
At the end of this process, a review of the analysis will be conducted to determine the extent to which readily available data and tools can be used to evaluate the effects of transit on the surrounding area. The results of the previous investigation will be coupled with knowledge about how the transit station changed the area around it in terms of travel behavior, land use and socioeconomic characteristics.
This will determine which effects were easily identified using census data and which went undetected during this analysis.
23 Results
The results section of the report will be divided into five parts. First, the location of the Green
Line Extension in context of the Boston area and existing transit services will be reviewed. Secondly, the variables that will be used to represent land use, socioeconomic characteristics and travel behavior will be given. These variables will then be used to present the existing conditions of the areas around the proposed Green Line Extension. The fourth section discusses the selection of the existing station and the control areas used for the comparison. Finally, the results of this comparison will be presented.
The Green Line Extension in Context
Before delving into an analysis of the proposed Green Line Extension, it is appropriate to review the line in the context of existing transit services and the larger urban area. The Green Line Extension is an addition to the already extensive system of rail lines serving the Boston area. Figure 3, shown below, shows the existing transit lines, the proposed line and their location within the towns of the Inner Core 2.
Of these lines, three – the Red, Blue and Orange Lines – are heavy rail, the Green Line is light rail and the
Silver Line is bus rapid transit. As the map shows, the existing lines do not serve the majority of
Somerville. Davis Square, a Red Line station located on the Somerville-Cambridge border, is the only existing station within the town boundary. Several other stations are close to the town and are within access to some of its residents, including Porter Square in Cambridge and Sullivan Square in Charlestown.
The proposed Green Line Extension, highlighted in the map, which runs through the center of the town, will service areas of Somerville that do not have access to the current transit system.
2 The Inner Core consists of twenty cities and towns within the metropolitan Boston area that are considered the most urban and populous within the Metropolitan Area Planning Commission (MAPC) planning area.
24
Figure 3 - Inner Core Towns and Existing Transit Services
Variables Used to Evaluate Station Areas
In order to conduct a complete analysis on the effects of transit, the data should cover three areas: land use, socioeconomic characteristics and travel behavior. Because a goal of this project is to determine the extent to which commonly available data can detect these effects, all data will be from the U.S. Census or MassGIS that is available through the Internet or library resources. The variables used in this analysis are presented in Table 3 3.
3 Land Use data is provided by MassGIS for the years 1971, 1985 and 1999. Further land use information for Somerville is provided by Joseph Ferreira on a parcel level for the year 2005. All other variables are available from the U.S. Census Bureau for the years 1970, 1980, 1990 and 2000.
25 Table 3 - Census variables used to track transit impacts (U.S. Census, MassGIS) Land Use Density Land Use Category Percentage of Persons 25+ years of age with 4+ years of Socioeconomic college Percentage of unemployed persons in the workforce Percentage of workers in managerial, professional or technical
occupations Median family income Median household income Median rent Median non-condominium housing value Percentage of vacant housing units Travel Behavior Percentage of workers who drive alone to work Percentage of workers who commute via public transportation Percentage of workers who travel 30+ minutes to work
The Existing Conditions of the Green Line Extension Station Areas
As mentioned in the methodology portion of the report, an accurate comparison between the Green
Line Extension project and an implemented transit station requires a similar level of service and initial population and land use characteristics. In this section, the expected level of service of the Green Line
Extension will be reviewed. Additionally, the population and land use characteristics of the transit corridor as a whole will be discussed and station areas with special considerations will be highlighted.
Level of Service of the Green Line Extension
The Green Line Extension, as a portion of the MBTA Green Line, is a light rail service. Light rail transit often has a lower level of service than heavy rail because it has lower capacity and lower travel speeds. However, the Green Line Extension will have a right of way through the travel corridor and thus will not have to interact with automobile or bus traffic on the street grid. This layout makes the service
26 faster and more reliable than a bus or even other portions of the Green Line, thus giving the Extension a higher level of service than other at-grade transit systems. It is important to note that some trips which begin on the Extension will continue through portions of the Green Line which do not have a right of way.
Thus, the level of service will depend on the destination location.
Characteristics of the Transit Corridor
The focus of this thesis, as stated in the introduction, is the town of Somerville. Therefore, the scope of the analysis on the Green Line Extension will be limited to those stations that will be accessible to Somerville residents, where accessibility is defined as the maximum walking distance of 400 meters.
The stations that meet this criterion are shown below in Figure 3.
Figure 4 – Proposed Green Line Extension Stations Accessible by Somerville (MBTA)
The majority of the transit corridor is characteristic of Somerville in terms of land use and population characteristics. As a metropolitan area, much of the land is already densely built out. Most of the station locations are surrounded by dense residential housing mix of mostly single- or multi-family
27 housing with a portion of apartment units and condominiums. The population densities of each station area as of 2000 are shown below. In addition to these figures, a density average of the Boston metropolitan area is also included to view the stations in the context of the larger region. As the figures show, all of the station areas have a higher density than the metropolitan average.
Table 4 - Population Density of Green Line Extension Station Areas (U.S. Census for 2000) Area Population Density (Persons/Acre) College Avenue 33.99 Ball Square 32.57 Lowell Street 30.64 Gilman Square 43.16 Washington Street 26.60 Union Square 29.40 Inner Core Average 26.79
The stations have a varying amount of non-residential parcels in the immediate area, including commercial, industrial and tax-exempt buildings 3. The land use classes of the parcels in Somerville, based on 2005 data, are shown in Figure 4.
Figure 5 - Land Use Categories of Somerville Parcels for 2005 (provided by Joseph Ferreira)
28 As is visible by this map, the areas immediately surrounding each station are largely residential.
Washington Street Station and Union Square Station differ slightly from the others, with more commercial and industrial parcels within the 400 meter buffers, which may account for the reduced population density compared to other stations.
In terms of socioeconomic characteristics, there is a wide range of values between the station areas. The values for each station area, as well as the Inner Core average, are shown in Table 5.
Table 5 - Socioeconomic Characteristics of Green Line Extension Station Areas (U.S. Census for 2000) Variable
Area Percentage of persons 25+ 25+ ofPercentage persons years 4+ yearsof with age (%)of college ofPercentage inunemployed persons the (%) workforce in ofPercentage workers managerial, professional or technical occupations (%) Income Median Family ($) Median Household Income ($) ($)Median Rent Median Non-Condo Housing ($) Value ofPercentage Vacant (%)Housing Units College Avenue 65.00 2.41 83.80 64,100 40,500 1470 255,000 4.42 Ball Square 40.80 2.31 72.60 63,400 56,700 980 284,000 2.67 Lowell Street 36.20 2.57 71.40 51,300 49,200 871 227,000 3.33 Gilman Square 30.10 2.46 66.40 49,300 44,300 823 231,000 3.10 Washington Street 23.50 2.10 67.40 35,500 30,900 762 198,000 5.38 Union Square 31.60 2.47 72.90 54,900 46,000 936 204,000 1.89 Metropolitan Average 37.50 3.28 74.00 61,900 51,500 858 240,000 3.61
The area around College Avenue Station has a noticeably higher median rent value, median family income and percentage of college graduates, most likely due to its proximity to Tufts University.
Similarly, Ball Square Station has higher income and land value figures above the metropolitan average.
On the other end of the spectrum, the area surrounding Washington Street Station has noticeably low land values and incomes. As a general trend, the remaining stations have socioeconomic characteristics which are at or below the Inner Core average.
29 Finally, in terms of travel behavior, residents who live near the proposed station areas have similar
commutes, and thus similar levels accessibility, to the Inner Core average. Each station area has
approximately 60 percent of residents driving to work. The areas also have approximately 20-20 percent
of workers using public transportation and 40-50 percent of workers with a 30+ minute commute. The
only station which does not exhibit these trends is College Avenue Station, since many residents work at
the nearby Tufts University.
Table 6 – Travel Behavior of Green Line Extension Station Areas (U.S. Census for 2000) Variable Percentage of workers Percentage of workers Percentage of workers Area who drive alone to work who commute via public who commute more (%) transportation (%) than 30 minutes (%) College Avenue 27.50 19.20 25.80 Ball Square 62.00 28.50 45.90 Lowell Street 65.90 25.10 49.40 Gilman Square 63.60 26.50 50.00 Washington Street 63.90 19.80 46.82 Union Square 52.70 23.90 41.20 Metropolitan 65.00 23.10 45.30 Average
While this level of accessibility may at first seem acceptable, Somerville’s density and close
proximity to Boston are both factors that make the town a more viable candidate for transit-oriented
development than other towns in the metropolitan area. Therefore, the fact that over half of workers drive
alone to work is due to the fact that there is a lack of accessible and reliable transit services in those areas.
Comparison of the Green Line Extension to an Existing Station
With a more complete picture of the line’s level of service and the profile of the population that
will be affected by the service, a comparison between the Green Line Extension stations and an already
implemented station can be conducted. The station chosen for this analysis is the only existing subway
station in Somerville, Davis Square Station.
30 The Red Line Extension
In 1984, the Red Line was extended through Davis Square, Somerville, connecting the Square to downtown Boston. The extension, like the rest of the Red Line, is a heavy rail service that offers travel speeds similar to or greater than that of the proposed Green Line Extension. Although the level of service of heavy rail is notably higher than light rail, this thesis treats the service of the Green Line Extension as comparable to the Red Line due to the fact that both services have a designated right of way.
Characteristics of the Transit Corridor
Before the area had access to transit services, Davis Square was similar to the Green Line
Extension station areas in the context of the larger metropolitan region. The center of the square was made up of commercial buildings, surrounded by dense residential housing. The density of the square in
1980 was 33.00 persons/acre, a significant jump from the Inner Core average of 25.50 persons/acre. The land use of Somerville in 1971, with a 400 meter buffer around the Davis Square station indicating the areas within walking distance of the service, is shown in Figure 5 below.
The initial land use and population characteristics of the Davis Square area in 1980, four years before the station was implemented, are shown in Table 7, along with the characteristics of the region during the same time period.
The socioeconomic conditions of Davis Square are similar to those of the proposed Green Line
Extension stations with income, employment and land value figures at or below the metropolitan average.
The travel behavior of the Davis Square residents denotes a level of accessibility that is slightly higher than that of the region, since there is a higher rate of public transportation use. However, the low percentage of commutes longer than 30 minutes suggests that workers may be employed close to their residence due to the lack of access to employment opportunities further away. With socioeconomic and
31 travel behavior variables similar to those of the Green Line Extension, the effects of the Red Line on
Davis Square’s residents can be used to predict Green Line’s effects on the other areas of Somerville.
Figure 6 - Land Use of Somerville in 1971 (MassGIS)
Table 7 - Characteristics of the Davis Square Area in 1980 (U.S. Census) Area Davis Metropolitan Variable Square Average Population Density (Persons/Acre) 33.00 25.50 Percentage of persons 25+ years of age with 4+ years of college (%) 21.40 21.30 Percentage of unemployed persons in the workforce (%) 3.10 3.20 Percentage of workers in managerial, professional or technical 59.90 61.00 occupations (%) Median Family Income ($) 19,500 20,200 Median Household Income ($) 15,600 16,500 Median Rent ($) 283 284 Median Non-Condo Housing Value ($) 45,400 50,200 Percentage of Vacant Housing Units (%) 4.48 5.71 Percentage of workers who drive alone to work (%) 41.50 45.50 Percentage of workers who commute via public transportation (%) 30.30 24.60 Percentage of workers who commute more than 30 minutes (%) 31.20 37.00
32 Controlling for General Economic Conditions
In order to accurately measure the effects of transit access on Davis Square, there must be a control for general economic conditions. This is necessary to ensure that the trends seen in land use, socioeconomic and travel behavior variables are caused by increased access and not other factors.
Incorrectly attributing these trends to accessibility will yield inaccurate results, overestimating (or underestimating) the effects of the transit service. This thesis will use two controls to ensure that this miscalculation does not occur – a regional average of the Boston metropolitan area and an area with transit access throughout the study period.
• Inner Core Average – The area used to track the trends of the region is the Inner Core, as defined by the Metropolitan Area Planning Commission (MAPC). The Inner Core consists of 20 cities and towns, including Somerville, which exhibit the unique characteristics and challenges of urban areas. This area is the correct scope of control, since a smaller region may not provide enough data points to be statistically accurate and a larger region would include suburban towns that may exhibit different trends than the study area.
• Transit Area Average – In order to ensure that areas with transit access evolved in the same manner as areas without transit access, neighborhoods around transit stations that were implemented significantly before 1980 will also be used as a control. This thesis uses three Green Line stations for this purpose – Summit Avenue Station in Brookline, Warren Street Station in Brighton and Babcock Street Station in Allston.
Summit Avenue Station – This station is a part of the Green Line “C” Branch, which was first opened in 1889.
Warren Street Station and Babcock Street Station – These stations are both part of the Green Line “B” Branch, which was opened in 1932.
It is important to note that the “B” and “C” branches of the Green Line have a lower level of service from the Green Line Extension because the lines do not have a right of way. Despite this difference, this thesis treats these stations as an accurate control for transit- accessible areas since the stations are so well established in their neighborhoods.
Results of Davis Square Analysis
In order to fully capture the effects of the Red Line Extension on Davis Square, data was collected before and after the implementation of the transit station. For the Davis Square station, which was
33 implemented in 1984, this was accomplished by collecting U.S. Census data from 1980, 1990 and 2000.
By monitoring neighborhood characteristics up to 16 years after implementation, the analysis hoped to capture gradual effects, such as a turnover of population or a difference in housing densities, as well as immediate effects, such as changes in commuting behavior. The results of the Davis Square analysis are presented in three sections: land use, socioeconomic characteristics and travel behavior.
Land Use
As mentioned before, changes in land use are accounted for through density changes. Since census data is residential based, land use changes can only be detected through changes in housing, as opposed to changes in commercial buildings. According to location theory, population density should increase with transit access due to the increased land value. Contrary to this expectation, the population density of
Davis Square decreased after 1984. The Davis Square results, as well as the control figures, are shown in
Table 8 and graphically in Figure 7. As the data shows, Davis Square is the only area which shows a decreasing trend through the 20 year time span. Although some areas have a slight decrease in 1990, the
Inner Core and the Green Line stations have a higher density in 2000 than in 1980. Davis Square, on the other hand, gradually decreases from 33.00 to 29.80 persons/acre during the same time.
34 Table 8 - Population Density from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Population Density Davis Square Inner Core Summit Avenue Warren Street Babcock Street 1980 33.00 25.50 38.20 62.20 42.90 1990 31.70 25.70 36.30 70.70 44.40 2000 29.80 26.80 41.20 70.60 46.10
80.00
70.00
60.00 Davis Square
50.00 Inner Core Summit Avenue
40.00 Warren Street Babcock Street
Population DensityPopulation (Persons/Acre) 30.00
20.00 1970 1980 1990 2000 2010 Year
Figure 7 - Population Density from 1980-2000 for Davis Square and Control Areas (U.S. Census)
Socioeconomic Characteristics
Changes in the socioeconomic status of residents are measured by land values and employment
statistics. According to previous research, access to transit leads to gentrification in the immediately
surrounding areas. This trend should manifest in housing statistics through increased non-condo housing
values and rents. In terms of employment, gentrification should increase the median income of the
neighborhood, lower the unemployment rate and increase the percentage of workers with white-collar
jobs. The results of this portion of the analysis are shown below, with housing variables presented first,
followed by employment variables.
35 Table 9 - Percentage of Vacant Housing Units from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Vacant Housing Davis Square Inner Core Summit Avenue Warren Street Babcock Street Units (%) 1980 4.48 5.71 3.02 7.91 3.72 1990 4.23 6.10 4.40 5.50 3.68 2000 3.41 3.61 3.09 1.14 3.82
10.00%
8.00%
Davis Square 6.00% Inner Core Summit Avenue 4.00% Warren Street Babcock Street Vacant Housing Units (%) Units VacantHousing 2.00%
0.00% 1970 1980 1990 2000 2010 Year
Figure 8 – Percentage of Vacant Housing Units from 1980-2000 for Davis Square and Control Areas (U.S. Census)
36 Table 10 - Median Non-Condo Housing Value from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Median Non-Condo Davis Square Inner Core Summit Avenue Warren Street Babcock Street Housing Value ($) 1980 45,400 50,200 89,400 47,200 68,800 1990 186,000 175,000 360,000 194,000 300,000 2000 330,000 240,000 344,000 196,000 295,000
$400,000
$350,000
$300,000
$250,000 Davis Square Inner Core $200,000 Summit Avenue
$150,000 Warren Street Babcock Street $100,000
Median Non-Condo Housing Value ($) Value Housing Non-Condo Median $50,000
$0 1970 1980 1990 2000 2010 Year
Figure 9 - Median Non-Condo Housing Value from 1980-2000 for Davis Square and Control Areas (U.S. Census)
37 Table 11- Median Rent from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Median Rent ($) Davis Square Inner Core Summit Avenue Warren Street Babcock Street 1980 283 284 357 275 356 1990 696 652 598 703 813 2000 1,000 858 1,220 915 1,260
$1,500
$1,250
$1,000 Davis Square Inner Core $750 Summit Avenue
Median Rent ($) MedianRent $500 Warren Street Babcock Street $250
$0 1970 1980 1990 2000 2010 Year
Figure 10 - Median Rent from 1980-2000 for Davis Square and Control Areas (U.S. Census)
These results confirm that the housing characteristics of Davis Square changed significantly after
the area gained access to transit. However, the data is less clear about whether these changes were caused
by the increased transit access, or whether they were the product of general economic trends. For two of
the three variables, percentage of vacant housing units and median rent, the trends that suggested
gentrification in Davis Square were also seen in the control areas. For the third variable, median non-
condo housing value, Davis Square did considerably deviate from the control areas. The median value of
the area increased over 700% from 1980 to 2000, whereas the Inner Core and the three transit control
areas increased less than 500%. Therefore, the housing statistics suggest that access to transit did, to some
extent, affect land values in Davis Square.
38 Table 12 - Unemployment Rate from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Unemployment Rate Davis Square Inner Core Summit Avenue Warren Street Babcock Street (%) 1980 3.05 3.21 1.75 2.96 2.96 1990 3.95 4.83 2.95 5.43 5.57 2000 1.12 3.28 0.95 1.51 8.45
10%
8%
6% Davis Square Inner Core Summit Avenue 4% Warren Street
Unemployment(%) Rate Babcock Street 2%
0% 1970 1980 1990 2000 2010 Year
Figure 11 – Unemployment Rate from 1980-2000 for Davis Square and Control Areas (U.S. Census)
39 Table 13 - Workers with White Collar Jobs from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Workers with White Davis Square Inner Core Summit Avenue Warren Street Babcock Street Collar Jobs (%) 1980 59.90 61.00 85.10 71.20 77.50 1990 76.30 67.20 87.60 64.00 77.60 2000 82.60 74.00 87.30 78.40 80.50
100.00%
90.00%
80.00% Davis Square Inner Core Summit Avenue 70.00% Warren Street
White Collar Jobs (%) Jobs Collar White Babcock Street 60.00%
50.00% 1970 1980 1990 2000 2010 Year
Figure 12 – Workers with White Collar Jobs from 1980-2000 for Davis Square and Control Areas (U.S. Census)
40 Table 14 - College Graduates from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Workers with White Davis Square Inner Core Summit Avenue Warren Street Babcock Street Collar Jobs (%) 1980 21.40 21.30 47.60 39.90 44.30 1990 46.10 30.80 60.60 44.60 71.30 2000 48.90 37.50 78.70 60.00 52.70
100.00%
80.00%
Davis Square 60.00% Inner Core Summit Avenue 40.00% Warren Street
College Graduates(%) College Babcock Street
20.00%
0.00% 1970 1980 1990 2000 2010 Year
Figure 13 - College Graduates from 1980-2000 for Davis Square and Control Areas (U.S. Census)
41 Table 15 – Median Household Income from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Median Household Davis Square Inner Core Summit Avenue Warren Street Babcock Street Income ($) 1980 15,600 16,500 16,900 10,700 14,900 1990 35,800 36,900 37,100 20,800 35,700 2000 55,900 51,500 58,600 34,400 43,200
$70,000
$60,000
$50,000
Davis Square $40,000 Inner Core
$30,000 Summit Avenue Warren Street $20,000 Babcock Street MedianHousehold Income($)
$10,000
$0 1970 1980 1990 2000 2010 Year
Figure 14 – Median Household Income from 1980-2000 for Davis Square and control areas (U.S. Census)
42 Table 16 - Median Family Income from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Median Family Davis Square Inner Core Summit Avenue Warren Street Babcock Street Income ($) 1980 19,500 20,200 24,200 14,000 18,400 1990 44,300 44,200 63,300 31,300 39,900 2000 67,500 61,800 90,300 41,800 49,800
$100,000
$80,000
$60,000 Davis Square Inner Core Summit Avenue $40,000 Warren Street Babcock Street Median Family Income ($) Income Family Median $20,000
$0 1970 1980 1990 2000 2010 Year
Figure 15 - Median Family Income from 1980-2000 for Davis Square and Control Areas (U.S. Census)
Similar to housing trends during the same time period, employment trends in Davis Square from
1980 to 2000 suggest that the socioeconomic status of the area’s residents increased slightly more than those of the control areas. The unemployment rate of Davis Square, which was similar to the Inner Core rate in 1980, decreased 64% over the next 20 years, whereas the Inner Core rate remained the same. Both the percentage of residents with a college degree and the percentage of workers with managerial, technical or professional jobs increased also, suggesting a shift in the type of residents that live in Davis Square.
This shift in the education and job type is accompanied by an increase in income, which is similar to or greater than shifts in the Inner Core and other transit areas.
43 Travel Behavior
The final set of results for the Davis Square analysis includes changes in travel behavior due to
increased access to transit. Increased access to the public transportation system is expected to shift travel
mode from single occupancy vehicles to transit, which will be monitored in the commuting patterns of
residents. Finally, commuting times may either increase or decrease with this mode shift; increases may
occur due to the fact that residents can access employment opportunities further away from their homes,
whereas decreases may occur if employment destinations stay the same, but commuters avoid road
congestion by using transit.
Table 167 - Percentage of Commutes via Automobile from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Percentage of commutes Davis Square Inner Core Summit Avenue Warren Street Babcock Street via automobile (%) 1980 41.50 45.50 37.10 26.20 34.10 1990 45.60 59.20 47.60 34.30 43.70 2000 42.40 65.00 46.80 46.60 31.90
80.00%
70.00%
60.00% Davis Square Inner Core 50.00% Summit Avenue Warren Street 40.00% Babcock Street Commutes via Automobile (%) CommutesAutomobile via 30.00%
20.00% 1970 1980 1990 2000 2010 Year
Figure 16 - Percentage of Commutes via Automobile from 1980-2000 for Davis Square and Control Areas (U.S. Census)
44 Table 178 - Percentage of Commutes via Public Transportation from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Percentage of commutes Davis Square Inner Core Summit Avenue Warren Street Babcock Street via public transportation (%) 1980 30.30 24.60 31.40 48.00 32.40 1990 36.80 15.10 26.00 42.80 21.60 2000 45.80 23.10 35.80 42.00 34.30
60.00%
50.00%
40.00% Davis Square Inner Core 30.00% Summit Avenue Warren Street 20.00% Babcock Street
10.00% Commutes via Public Transportation (%)
0.00% 1970 1980 1990 2000 2010 Year
Figure 17 - Percentage of Commutes via Public Transportation from 1980-2000 for Davis Square and Control Areas (U.S. Census)
45 Table 189 - Percentage of Commutes Longer than 30 minutes from 1980-2000 for Davis Square and Control Areas (U.S. Census) Area Percentage of commutes Davis Square Inner Core Summit Avenue Warren Street Babcock Street longer than 30 minutes (%) 1980 31.20 37.00 47.70 51.20 37.70 1990 43.50 38.50 40.00 50.20 32.50 2000 48.90 45.30 47.60 59.10 40.20
70.00%
60.00%
Davis Square 50.00% Inner Core Summit Avenue 40.00% Warren Street Babcock Street
30.00% Commutes longer than 30 minutes (%)
20.00% 1970 1980 1990 2000 2010 Year
Figure 18 - Percentage of Commutes Longer than 30 minutes from 1980-2000 for Davis Square and Control Areas (U.S. Census)
These results confirm the assumption that the Red Line Extension into Davis Square significantly
changed commuting patterns after 1984. The area has had a steady percentage of workers who commute
via automobile, as opposed to the Inner Core, which has seen a 20% increase in automobile commutes
over the study period. More striking is the percentage of Davis Square residents who commute via public
transportation, which has increased from 30% in 1980 to over 45% in 2000 while Inner Core commutes by
transit have actually decreased. This increased access to transit led to longer commuting times for Davis
46 Square residents, where the increase in the percentage of commutes longer than 30 minutes is significantly greater than the control areas. From 1980 to 2000, the figures for Davis Square rose from 31% to 48%, whereas the next biggest increase was from 37% to 45% for the Inner Core.
47 Discussion
This portion of the report will discuss the significance of the results from the Davis Square analysis and attempt to use these results to project the effects of the Green Line Extension on the proposed station areas. As the data suggests, the effects of transit access on Davis Square, and how these effects apply to the proposed project, are not obvious; therefore, a more extensive look at what these data trends mean for the affected residents in the community is in order.
Discussion of the Davis Square Analysis Results
The analysis of Davis Square from the years 1980 to 2000 shows that increased access to transit affected the lives of the area’s residents far beyond the scope of transportation – in fact, the results suggest that the transportation project may have caused a shift in the type of people that live in Davis Square. A discussion of the results is presented below, with land use effects first, followed by socioeconomic characteristics and travel behavior.
Land Use
As mentioned in the Land Use portion of the Results section, the density changes in Davis Square since the Red Line Extension are not as expected. The data show a decreasing population density in the area since 1980, dropping from 33.00 persons/acre to 29.80 persons/acre. Furthermore, this was not a regional shift in density, as all of the control areas’ densities increased during the same time period.
However, this result is contrary to location theory, as the benefits of transit access should attract residents to the area.
Before discussing the possible reasons for which the analysis produced results contrary to the expected results, an overview of the policies guiding residential and commercial density is warranted.
Throughout the study period, Somerville kept a fairly low floor area ratio (FAR) of 2.0 and a building height restriction of 50 feet, which caused development in Davis Square to be gradual (City of
48 Somerville). These policy decisions have capped the extent to which interest in profiting off of the benefits of transit access can affect development, preventing projects such as high-tower apartment complexes from significantly increasing the density of the area.
With this context in mind, this thesis proposes that the unexpected result in the analysis may be due to insufficient land use data. In order to conduct a time-series analysis on the population density of
Davis Square from 1980 to 2000, one needs both the population for each decade, as well as the size of the residential area in which this population resides. Population density can fluctuate due to either 1) a change in the number of people living in the area or 2) a change in the area of land designated as residential. The U.S. Census on a census block level provided the population data for this analysis and
MassGIS provided the land use data with a minimum mapping unit of one acre. Because MassGIS created the land use file using 1:25,000 to 1:40,000 aerial photography, the categorization in the map is fairly low resolution and does not pick up subtle land use changes. Under this low resolution, the Davis
Square area was shown to have no land use changes during the study period. Accordingly, the area used to calculate the population density remained the same.
This set up may have led to an inaccurate calculation of the population density of the area because the analysis did not account for subtle changes in land use that could have occurred in Davis Square after the Red Line Extension. Once the station was constructed, portions of areas that were once residential may have become mixed use or commercial, as businesses were drawn to the accessibility of the Davis
Square area. Therefore, the area in which residents could live decreased and the types of housing in the area changed from single- or multi-family houses to denser residential housing, such as apartments or condominiums. With this larger context, it is possible that while the actual population of the Davis Square region decreased, the density at which this population resided may have increased.
49 Socioeconomic Characteristics
The results of the analysis confirm the assumption that, since Davis Square gained access to the
Red Line, the socioeconomic status of the area’s residents has changed dramatically. However, the analysis does not confirm how these changes in land value and income correspond to the turnover rate of residents. While it’s possible that the socioeconomic status of pre-1984 residents increased during this time period, it’s more likely that pre-1984 residents with low-socioeconomic status were replaced with new residents who could afford the increasing land values of the area.
Once the transit station was constructed in Davis Square, the land values of the area increased due to the benefits of living in a transit-accessible area. As shown in the results section, the land values of the
Davis Square area were equal to the Inner Core median values in 1980, and then rose above the regional average by 1990 (See Tables 10 and 11). If the cost of renting an apartment or owning a house increased disproportionately more than cost of transportation decreased, the net cost of living in Davis Square increased after 1984. The residents living in the area before this change had a median income below the
Inner Core average (See Table 7) and were potentially unable to afford this increase in living costs. As the results show, over the next decade, the median socioeconomic status of residents in the area increased greater than did the regional average. Cherie Abbanat, a resident of the area, notes that the area has seen a shift from blue-collar workers to white collar workers living in the area since the implementation of the station (2009). As these blue-collar workers moved out of the area, the number of kids living in the area also decreased as many of the workers had families. A possible reason for this shift is that, gradually, the pre-1984 residents may have been replaced by new residents with higher incomes who could afford the higher living expenses associated with living in Davis Square. In this scenario, the socioeconomic changes recorded in Davis Square would not have happened simultaneously; instead, the land values
50 increased first, followed by increased income levels and employment statistics. However, because data for the study period gave only one figure per decade, it is difficult to determine the sequence of events.
It is also important to note that this analysis did not include the effects of increased accessibility on commercial property values, since this analysis focused on Census data. Access to a commercial or office building is beneficial for a business, because of the ease at which an employee, client or consumer can reach the location. Therefore, it is likely that commercial property values increased along with residential property values. This calculation is important to include in a cost-benefit analysis for a transit project, as increases in commercial property values will generate tax revenue for the government.
Travel Behavior
As expected, the trends in travel behavior denote an increased level of access for residents in Davis
Square with the implementation of the transit station. Throughout the study period, the number of residents who chose to drive alone to work did not increase, whereas the Inner Core increased 20%.
Furthermore, almost half of Davis Square residents chose to use public transportation for their daily commute. These figures confirm the assumption that after 1984, residents of Davis Square had easy access to public transportation and made use of this access in their day-to-day travels.
This embrace of public transportation is seen indirectly through the increase of commutes longer than 30 minutes. The two potential reasons for this increased commuting time are either 1) that it takes longer to get to a certain location via transit than automobile, or 2) residents chose to work further away from their homes due to the increased access to other Inner Core towns. Because census data does not provide information on where residents are employed, it is not possible to rule out either of these scenarios. However, due to the constant traffic congestion on the major roads throughout the Inner Core, it is unlikely that trips via transit (with right-of-way) take significantly longer than those made via automobile.
51 Finally, it is important to note that this analysis was not able to account for increased access to
Davis Square by non-residents. As mentioned in the literature review, locating a transit station in a neighborhood produces both source and sink benefits – that is, residents can more easily travel from the area and non-residents can more easily travel to the area. Because the census is residential-based, there was not data available to account for the “sink” effects. Travel time savings for non-residents is an important benefit of any transit project and should be included in a cost-benefit analysis when justifying the public funds needed for the investment.
Application to the Green Line Extension
With a clear picture of how the residents of Davis Square were affected by the Red Line
Extension, one can more accurately forecast how the Green Line Extension will affect those living in proposed station areas. The degree to which land use, socioeconomic characteristics and travel behavior change will depend upon numerous factors, including land use and zoning policies set by the Somerville government, the level or service of the Green Line Extension and the socioeconomic make-up of residents currently living in the station areas.
Land Use
As mentioned in the Discussion section of this report, the analysis of Davis Square may not have accurately portrayed the land use changes that occurred in the area after the Red Line Extension.
However, through research on the area and the applicable land use policies, it is clear that the low FAR limits and height restrictions on buildings in the area led to a gradual increase in residential density and commercial development in the decades after the station was put in place. It follows that the degree to which density increases near the Green Line Extension stations areas will depend upon the land use policies set in place by the Somerville government. If Somerville enacts FAR limits and height restrictions similar to those in Davis Square, it is likely that development will be gradual.
52 However, if Somerville plans to enact high FAR limits and increased height restrictions, development is likely to occur more abruptly. This is true for Union Square, where the Somerville government is proposing an FAR limit of 5.0 and general height restriction of 70 feet 4 (Somerville
Government), as opposed to Davis Square’s 2.0 FAR and height restriction of 50 feet. From the perspective of the government, this will create revenue that will compensate for the costs of the project.
Many residents, however, believe that this decision will result in unmanageable growth that will overwhelm the people and the businesses that are currently there.
The degree to which land use will change also depends on the current mixes of land use in the station areas. As mentioned in the Results section, the station areas have different mixes of commercial and residential zoning. Those areas that are predominantly residential will likely see an influx of commercial uses, whereas those that are already fairly mixed use will stay relatively the same. Below is a summary of the likely land use changes for each station:
• College Avenue – The majority of residents around this station are associated with Tufts University. It is likely that a large portion of the station area will remain residential, as these residents will not be able to relocate away from the University. The station area also has a large portion of tax-exempt land, which may be turned into commercial or residential use so that the government can benefit from increased land values.
• Ball Square – This station area is largely residential with a few commercial buildings. It is likely that transit access will promote more commercial uses in the area.
• Lowell Street – Like Ball Square, Lowell Street is largely residential with some commercial and industrial buildings. The Extension will likely lead to more commercial and industrial uses in the area.
• Gilman Square – This area is mainly made up of tax-exempt uses. It is possible that the current owner of this land will sell it to a business or real estate company in order to benefit from the accessibility of the area. However, if it is a longstanding building, such as a religious center, the owner may keep the property.
4 The city’s plan has recently reduced its proposed maximum height to 70 feet, but still allows 85-foot height limit along Prospect Street in the square and 100 feet for “green construction”.
53 • Washington Street – This area is fairly mixed use, with many commercial buildings and a dense residential housing. Therefore, the land use will not be greatly affected by the project.
• Union Square – As mentioned above, the Somerville government has big plans for Union Square. If the proposed zoning policies go through, the area will see an increase in commercial and high-density residential buildings.
Socioeconomic Characteristics
As the Davis Square analysis showed, the socioeconomic makeup of Davis Square residents changed significantly after the area gained access to transit. The degree to which the Green Line
Extension will affect the socioeconomic status of the station areas’ residents will depend on the level of service of the line.
As the literature review discussed previously, accessibility to transit services can lower a resident’s transportation costs if the service removes the need for a car. The Red Line, as a heavy rail service, offers the highest level of transit service, due to its reliability and right of way. Furthermore, the Red Line travels through the heart of downtown Boston, with a direct route to Park Street and Downtown Crossing.
The Green Line Extension, although a light rail service, has the potential to offer a comparable level of service. Because the Extension has a right of way up until downtown Boston, all trips made to and from the central business district will have travel speeds similar to heavy rail. It is possible that delays may occur if cars are held up from other portions of the Green Line that do not have a right of way. Portions of the line are notorious for having slow travel speeds and heavy delays, so this effect should be taken into account. Furthermore, the Green Line does not have a station at such a central location as does the Red
Line. However, the line does stop at North Station, which allows transfers to the Red Line. Therefore, the
Green Line is not significantly less convenient than the Red Line.
54 With this level of service in mind, it is likely that land values around Green Line Extension stations will increase as much as, or slightly less than, did those around Davis Square. Similarly, income and employment impacts will likely be similar to or less than those in Davis Square.
Travel Behavior
The results of the Davis Square analysis confirmed that the Red Line Extension drastically changed residents’ travel behaviors, increasing the percentage of commutes via public transportation while keeping the percentage of commutes via automobile constant. The extent to which transit access will affect travel behavior is dependent on the line’s level of service. If commuters view the service as reliable and quick, they will be more willing to use it to while traveling to their places of employment. However, if the service is unreliable or have slow travel speeds, commuters will likely continue to use their cars to go to work.
As mentioned above, the Green Line Extension has the potential to have a level of service comparable to that of the Red Line. It follows that the effects on travel behavior caused by Red Line
Extension into Davis Square will be comparable to those which will be caused by the Green Line
Extension.
55 Conclusions
Throughout the world, public funds are being invested into transit projects with the hopes of increasing access and mobility while improving the environment. The Green Line Extension, currently under consideration, is no exception – the project aims to increase regional mobility and access to the residents of Somerville, Cambridge and Medford, Massachusetts, while improving air quality and reducing greenhouse gas emissions. With these issues in mind, the goal of this thesis was to explore the extent to which the benefits of transit projects can be measured using commonly available data.
In order to investigate the impacts of a line that is not yet constructed, a comparison of an already implemented transit station was completed using data available from the U.S. Census Bureau and
MassGIS. Davis Square, a transit station in Somerville implemented in 1984, was chosen due to its similarities to the Green Line Extension corridor in terms of initial population characteristics, land use and level of service. Characteristics of the station area and its residents were compiled before and after the implementation of the station and compared to control areas to determine the effects of increased transit access on land use, socioeconomic characteristics and travel behavior.
The results of the analysis confirmed that transit access increased land values in the area, which led to an influx of wealthier residents who could afford to pay these higher rents and housing prices. The data also showed that the addition of a reliable and fast transit service in the area allowed many commuters living in Davis Square to use public transportation to travel to work as opposed to their automobiles.
While these results were conclusive and agreed with firsthand knowledge of how the area changed, certain aspects of the analysis were misleading or incomplete due to insufficient data. The analysis results suggested that population density in Davis Square decreased over the study period, which is contrary to location theory, as well as firsthand knowledge of the area. Furthermore, the analysis of the Red Line’s
56 impacts on land values was limited to residential impacts, excluding changes in rent for commercial buildings. Finally, accessibility benefits from the Extension were limited to those benefits seen by residents of Davis Square and did not include benefits for travelers who are coming from other areas of the Inner Core.
This exercise has shown that, through commonly available data and analytical software, the potential for non-professionals to investigate the impacts of transit projects on surrounding communities has expanded greatly over the past decade. Census data is particularly useful in tracking changes in residential characteristics, such as housing, employment and travel behavior. However, these data are far from comprehensive. Important information regarding subtle land use changes, commercial land values and “sink” accessibility effects are overlooked when conducting an analysis based on residential data and high-level land use data.
While this analysis was not able to comprehensively capture the effects of the Red Line Extension, the types of data which are available are still expanding. Increased employment and trip destination data has the potential to capture the “sink” effects of transit projects. Furthermore, commercial property data can allow a future analysis to include transit’s impact on commercial land values. These new data will allow a future analysis to cover regional and local effects that were not included in this project.
Although the amount of publicly available information is continuously expanding, an accurate and contextual analysis requires experience and knowledge of the study area. Raw data must be coupled with regional information, such as land use policies and the level of transit service, in order to fit into the larger context. Therefore, despite the availability of data, a professional analysis is still, and may always be, necessary to create a complete picture of how a transit project will affect the land in the immediate vicinity of the station, as well as the larger region.
57 Bibliography
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Alonso, John G. “Public-Private Joint Development at Rapid Transit Stations.” Transportation Quarterly 40, 3: 317-31. 1986.
Beaton, Eric. “The Impacts of Commuter Rail on Greater Boston.” Rappaport Institute of Greater Boston. PB-2006-4. September 2006.
Belzer, Dena and Autler, Gerald. “Transit-Oriented Development: From Rhetoric to Reality.” The Brookings Institute Center on Urban and Metropolitan Policy. June 2002.
Bowes, David et al. “Identifying the Impacts of Rail Transit Stations on Residential Property Values.” Journal of Urban Economics 50(1) July 2001, Pages 1-25.
Calgary Transit Division. “Transit Friendly Design Guide.” Calgary City Council. April 2006.
Center for Environmental Excellence. “Environmental Justice – Overview.”
Cervero, Robert et al. “Transit’s Value-Added: Effects of Light and Commuter Rail Services on Commercial Land Values.” Transportation Research Board . November 2001.
City of Somerville, Massachusetts. Code of Ordinances.
Dagang, Deborah. “Transportation Impact Factors – Quantifiable Relationships Found in the Literature.” JHK & Associates for Oregon DOT. 1995.
Debrezion, Ghebreegziabiher et al. “Impact of Railway Station on Dutch Residential Housing Market.” European Regional Science Association , Number ersa05p748. August 2008.
Diaz, Roderick. “Impacts of Rail Transit on Property Values.” APTA 1999 Rapid Transit Conference. May 1999.
Dunphy, Robert et al. “Transportation, Congestion and Density: New Insights.” Transportation Research Board: Journal of the Transportation Research Board. Vol. 155 January 2007, Pages 89-96.
Giuliano, Genevieve. “Land Use Impacts of Transportation Investments: Highway and Transit.” In The Geography of Urban Transportation, Susan Hanson, ed. New York: Guilford. 1986.
Green Line Extension. Project History.
58 Hammel, Daniel and Wyly, Elvin. "A Model for Identifying Gentrified Areas with Census Data" Urban Geography Vol. 17 2006.
Lin, Jeffery. "Gentrification and Transit in Northwest Chicago." Journal of the Transportation Research Forum, in Transportation Quarterly 56 2002, Pages 175-191.
Litman, Todd. “Land Use Impacts on Transport: How Land Use Factors Affect Travel Behavior.” Victoria Transport Policy Institute. November 5, 2008.
MassGov. “Transit Oriented Development (TOD) Urban Case Study”. http://www.mass.gov/envir/smart_growth_toolkit/pages/CS-tod-somerville.html. Last accessed March 23, 2009.
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59 Appendix
This appendix reviews the resources used to collect residential and land use data for the time-series analysis, as well as the methodology used to analyze this data. In the first section, information about the data layers used in the Davis Square analysis will be presented. The second section discusses the geographic boundaries of the analysis. Finally, the methodology for processing this data will be reviewed.
Data Collection
As mentioned throughout the thesis, the purpose of this project was to determine the extent to which commonly accessible data can be used to analyze transit projects. Therefore, the analysis of Davis
Square relied on data available from the U.S. Census Bureau and MassGIS, the Commonwealth’s Office of Geographic and Environmental Information.
Land Use Data
Information regarding the land use of Inner Core towns was obtained through MassGIS’s website.
The MassGIS Land Use data layers have both 21 and 37 land use classifications (depending on the desired level of detail), which was created from 1:25,000 aerial photography. The layer has statewide coverage for 1971, 1985 and 1999. Finally, the Somerville government provided a parcel-level layer of Somerville land use.
Residential-Based Data
The U.S. Census Bureau provided all data used in the analysis regarding changes in residential characteristics. Although portions of the 2000 census are available on the Bureau’s website, Geolytics was used to access long-form census data from 1980, 1990 and 2000. Geolytics provides census demographics for social researching and is commonly available through library resources.
60 Geographic Boundaries
In order to accurately measure the changes in land use and residential characteristics in Davis
Square and the control transit station areas, the geographic boundaries of the analysis should be as detailed as possible. Due to the various sources of data, variables used for the analysis were not all available on the same level of detail. Therefore, an explanation of the level of analysis for each area is provided.
Land Use Data
In the case of land use, data would ideally include all land within walking distance from the transit station and be clipped where this access ends, which is 400 meters away from the station. However, the
MassGIS land use layers are fairly high level, with a minimum mapping unit of one acre. Therefore, the analysis included all land use areas that overlapped at all with the 400-meter buffer of the station area.
Residential-Based Data
For residential-based data, the ideal geographic limits would be residential areas within the 400- meter buffer of the transit station.
Data Processing
This analysis was performed using ArcMap, Microsoft Access and Microsoft Excel. All census data used in this project was collected from Geolytics on a blockgroup level and imported into ArcMap.
This data was then joined to the census blockgroup layer in ArcMap. As mentioned above, the buffer boundary for each transit station was used to create ratios for each block group denoting the portion of the block group with access to the facilities.
Data for each blockgroup was then imported into Access. In Access, a variable’s value for each blockgroup was multiplied by the appropriate ratio; the variables were then aggregated into two tables
(one for socioeconomic characteristics and one for travel behavior) to be imported back into ArcMap.
61 With these tables, a preliminary median value for each variable was determined using ArcMap’s statistical tools.
These preliminary median values were brought into Excel, where they were divided by the sum of the ratios used in Access. These final values were aggregated into tables in Excel, which were used to measure the changes in each transit area over the study period.
62