Land Use Impacts of Bus Rapid Transit: The Boston Silver Line
Victoria Perk, Senior Research Associate National Bus Rapid Transit
Institute Center for Urban Transportation Research University of
South Florida, Tampa Steven Reader, Ph.D., Associate Professor
Department of Geography, Environment, and Planning University of
South Florida, Tampa GIS in Public Transportation Conference
September 14, 2011 St. Petersburg, Florida
Slide 2
Can bus rapid transit (BRT) impact surrounding land uses and
property values in a similar way as light rail transit (LRT)? Issue
of permanence of services & facilities Research Objective
Slide 3
BRT is an enhanced bus system that operates on bus lanes or
other transitways in order to combine the flexibility of buses with
the efficiency of rail. BRT operates at faster speeds, provides
greater service reliability and increased customer convenience. BRT
uses a combination of advanced technologies, infrastructure and
operational investments that provide significantly better service
than traditional bus service. What is Bus Rapid Transit? Source:
Federal Transit Administration
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Integration of Elements BRT Elements
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BRT in the U.S.
Slide 6
Before 2009, no recent quantitative modeling studies on
property value impacts of BRT in the U.S. Previous studies address
impacts of rail modes on property values Isolate effect of distance
from transit (either right-of-way, stations, or both) Typical
results find positive impacts on property values from nearby rail
transit, but magnitudes are relatively small Previous Work
Slide 7
We hoped to find statistically significant, positive impacts on
surrounding property values from BRT, with magnitudes approaching
those found for rail transit modes. Estimate the impacts of BRT on
surrounding property values using hedonic regression models
Estimate the variation in property values due to proximity to BRT
stations Isolate the effect of distance to nearest BRT station from
all other (measurable) factors that determine property values
Hypothesis & Method
Slide 8
Pittsburgh Martin Luther King, Jr. East Busway Hedonic
regression model, statistically significant results, using data
within -mile of BRT stations Moving from 101 to 100 feet from a
station increases market value of single-family home by $19.00
Moving from 1,001 to 1,000 feet from a station increases market
value of a single-family home by $2.73 Next application: Boston
Silver Line First Application
Slide 9
Boston Rapid Transit
Slide 10
Branded as part of MBTAs rapid transit system Low-floor 60 ft.
CNG vehicles Exclusive bus lanes 10-minute peak frequency 15-minute
off-peak frequency Real-time passenger information Transit signal
priority Phase I Washington Street opened July 2002 Phase II
Waterfront opened December 2004 Proposed Phase III to connect the
two Boston Silver Line
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As the first phase of the Silver Line, this corridor was
selected for research Replaced MBTA Route 49 Two routes operate
along the corridor: SL4 & SL5 Provide two options into Downtown
Boston 14 stations Approximately 15,500 daily boardings Boston
Silver Line Washington Street Corridor
Slide 13
Parcel data from City of Boston Assessing Department, 2003-2009
Sales transactions of condominium units from the City of Boston,
2000-2009 U.S. Census data Data set constructed using GIS Used only
parcels located within one quarter-mile of the Washington Street
corridor Data set contains approximately 5100 sales transactions
from 2000 to 2009 Data
Slide 14
Data Sources GIS Parcel Layer - 2007 Property Appraiser
Database Sales Data
Slide 15
Use of GIS in the Project Data Matching Identification of
Condominium Main Parcel using Point- in-Polygon (spatial join) b/w
sales data points and GIS Parcel Layer 2007, clipped to buffer
around BRT Line Use of Table Relates to relate b/w Condominium Main
ID from sales data and multiple years of Property Appraiser Data,
for identification of specific condominium unit IDs and
characteristics thru time.
Slide 16
Use of GIS in the Project Network Analysis Condominium property
parcels generalized to centroids Shortest-path road network
distances calculated in ArcGIS Network Analyst based on above
centroids, ESRI StreetMap database for 2008, and BRT stations as
destinations
Slide 17
Parcels within Mile Buffer of the Boston Silver Line BRT
indicating Condominium Parcels with Sales 2000-2009
Slide 18
Condominium Parcels within mile of Silver Line with Sales
2000-2009 (n=563)
Slide 19
Condominium Parcels within mile of Silver Line with Sales
2000-2009 Built after 1997, by Year Built (n=37)
Slide 20
TypeNumber ParcelsNumber Sales Built before 1998, not
remodeled3332271 Built before 1998, remodeled after 19971931010
Built after 1997371828 Totals5635109 Built after 1997, with 40+
sales 2000-2009*111515 Number of Condominium Sales (2000-2009)
within mile of Boston Silver Line BRT by Type of Parcel
Slide 21
Condominium Parcels within mile of Silver Line with 40+ Sales
2000-2009 Built after 1997, by Year Built (n=11)
Slide 22
Median Price Per Square Foot by Year for All Condominium Sales
within mile of Boston Silver Line BRT
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Dependent variable: sale price per square foot Key independent
variable: network distance of parcel to nearest BRT station Other
variables Property characteristics Neighborhood characteristics
Local housing price index Variables
Slide 29
Results
Slide 30
Hedonic regression models using sales from years 2000, 2001,
and 2002 indicate that price per square foot was higher for condos
further away from the corridor, but this relationship was not
statistically significant. Beginning in 2003, after the opening of
the Silver Line Washington Street, similar models begin to show a
statistically significant inverse relationship between distance to
a BRT station and sale price per square foot. Results, contd
Slide 31
2007 sales indicate a premium of $0.18 per square foot for each
foot closer to a BRT station 2009 sales indicate a premium of $0.11
per square foot for each foot closer to a BRT station (although
this result is only significant at the 90% level) These
relationships exhibit decreasing marginal effects, meaning the
effect diminishes farther from the stations Results, contd
Slide 32
With recent research on BRT in Pittsburgh and the Boston Silver
Line, we are beginning to show that proximity to BRT stations can
have a positive effect on residential property values and sale
prices. These effects are very similar to those shown in the
literature for LRT Conclusion
Slide 33
A report on this research will be available later in the Fall
Additional work will begin on further analyzing the Boston data, as
well as data from other cities with BRT such as Cleveland Work
underway this year to update information on local, regional, and
state policies and plans related to transit and development For
more information please visit www.nbrti.orgwww.nbrti.org Upcoming
Work