This document provides an overview of transit-oriented development (TOD), including its definition, types, goals, planning considerations, case studies, and how its effects are measured. TOD aims to maximize access to public transport through compact, mixed-use development near transit facilities. Case studies discussed include developments in the US, Brazil, and Australia that incorporated TOD principles like density, mixed uses, walkability and public transport access to achieve goals like increased ridership and reduced automobile dependence. A variety of indicators are used to measure TOD outcomes, such as ridership, vehicle ownership, and accessibility.
Measuring Effects of Transit-Oriented Developments
1. Management and Prediction Demand
Homework : TOD
Kwikiriza Bruce Chris
Universiteit Hasselt
December 18, 2015
2. Management and Prediction Demand
Contents
1 Introduction
2 Planning
Sustainability and Development of TODs
3 How TOD effects are measured
4 Case Studies
5 Thank you
6 References
3. Management and Prediction Demand
Introduction
Introduction
Transit-oriented development (TOD) definition
Mixed-use of residential and commercial area designed to
maximize access to public transport (Newman & Kenworthy,
1988)
often incorporates features to encourage ridership
compact, mixed-use development near transit facilities and
high-quality walking environments (Cervero, 2008)
should be developed in higher density places.
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Introduction
Types of TOD
According to Dittmar & Poticha, (2004),
TODs include the following:
urban neighborhood
urban downtown/urban center
suburban town center
suburban neighborhood
neighborhood transit zone
commuter town.
special use/employment district
mixed-used corridor
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Introduction
Scientific questions
What are the goals of TOD?
How to implement and plan for TOD?
How are the TOD goals measured?
What indicators are used to measure the effects of TOD?
Which effects must be taken into account?
8. Management and Prediction Demand
Introduction
Objectives/Goals of TOD
Enhance livability,
Foster wider housing choices,
Provide private development opportunities, safer
neighborhoods,
Reduce parking requirements,
Improve air quality
Promote intermodal integration.
9. Management and Prediction Demand
Introduction
It increases ridership
Reduces automobile dependence item Increases sustainability.
Promotes the integration of land use and transit facilities.
It increases accessibility.
Pedestrian safety since there is no traffic congestion
It Reduces congestion on the road network
It reduces travel time
10. Management and Prediction Demand
Planning
Considerations while planning for TODs
According to Boarnet & Compin, (1999) variables that should
be considered when planning for and implementing
development around transit station areas include:
Population and employment density
Intensity and diversity of land uses
Parking availability
Physical design of the street
connectivity and accessibility
Exhibit Compact Building Design
11. Management and Prediction Demand
Planning
Provide ranges of housing types
Promote “walkable” neighborhoods
Exhibit a distinct sense of place
Preserve open space
Utilize existing development
Provide transportation choices
Practice fair decision-making
Promote stakeholder participation
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Planning
Aspects to be focused on by Developers before
Commisioning the Project (TODs)
High density places with rail stops and bus stops
The environmental and design factors are important aspects in
contributing to the success of TOD projects.
Assistance and cooperation of government agencies.
The presence of adequate policies to address issues of traffic
pollution and congestion (Cervero & Day, 2008) .
Public and private sector involvement
The transit agencies and local land use promoters of TOD.
Funding (Intensive capital)
13. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Diversity (Land use mix)
commercial Services
retail services
jobs
community infrastructure(Cervero, & Kockelman, 1997)
open space (Recreation)
14. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Density(Land use)
Higher density residential uses
increase vitality (Liveliness)
provide more convenient access to public transport services.
According to(Weisbrod & Treys, (2008) the following baseline
density guidelines have been proposed.
activity centers: 40–120 dwellings per hectare (net) or greater
suburban and neighborhood locations: 30–80 dwellings per
hectare (net) or greater
priority transit corridors: 40 dwellings per hectare (net) or
greater
15. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Design(Ensuring development features)
High-quality subtropical design
maximizes public amenities like schools, hospitals etc.
Quality of streets
pedestrian connectivity
Walking and cycling lanes
high levels of accessibility
16. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Barriers that Hinder the development of TODs
The transit agencies developers under appreciate ability to
overcome the land assembly.
Project financing barriers (Limited intensive capital)
Problem of converting capital investment into positive
operating returns
Public sector involvement and TOD developers are
discouraged by, community opposition to high-density places.
unattractive locations and heavily industrialised neighborhoods.
Fixation on automobile-oriented design (McNulty et al, 1997).
17. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Importance of TOD
It increases ridership / public transport
It increases revenues to Government.
It reduces automobile usage
It reduces the volume of vehicles
It reduces congestion on the road
It offers a wide variety of housing/residential houses.
18. Management and Prediction Demand
Planning
Sustainability and Development of TODs
It reduces rent rates and thus increase in property
values(Cervero et al., 2002)
TODs contributes to a greater mix of land uses
It acts as a recreation centre like BART’s Pleasant Hill station.
Increases the amount of housing, office space, and community
retail in close proximity to the station (Cervero et al., 2002)
Reduces emission pollution
19. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Effects of Transit oriented development
Increases accessibility
Increases ridership
Reduce highway transportation costs and externalities such as
road maintenance and infrastructure expenses, as well as
Reduce emission pollution
Reduce noise pollution
Reduce fuel consumption.
It reduces transportation costs because of housing location
choices (Weisbrod & Treyz,2003).
5% reduction in commute time has the same effect as a 1.5%
decrease in rent or 28% reduction in home value (Weisbrod &
Treyz,2003).
20. Management and Prediction Demand
Planning
Sustainability and Development of TODs
Negative Effects of TODs
Delays due to many stops hence increases travel time
Over crowding of passagers
Public transport is expensive
Higher level of crime (Dittmar & Poticha, 2004)
Deterioration of livability values due to increased density
Increase on real estate prices.
Inconsistency in the time schedule (time table)
21. Management and Prediction Demand
How TOD effects are measured
Ridership
Vehicle ownership
Resident commuting
Transport-related perceptions of residents
Travel Behaviour
CO2 emissions (computed)
Park space
22. Management and Prediction Demand
How TOD effects are measured
Accessibility
Vehicles kilometres travelled (VKT)
Frequency of public transit usage
Street Quality
Pedestrian accessibility (pedestrian shed)
Amount and quality of public space(networks)
Infrastructural distribution and Development
23. Management and Prediction Demand
How TOD effects are measured
Livability
The Local Economy
Number of jobs by type
Vacancy rate
Quality of transit service
Quality of life (resident perceptions)
Home ownership vs. rental
Weekly housing expenses
Quality of Education
Income levels
24. Management and Prediction Demand
How TOD effects are measured
Congestion Pollution
energy(fuel) consumption (computed)
Percent of land cover as green space
Percent of land cover as trees
Accelerating and Decelerating
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How TOD effects are measured
Development
Property value
Population and housing density
Land cover/land use distribution
Parking inventory
The Social Environment
Policy abidance e.g stockholm congestion pricing
26. Management and Prediction Demand
How TOD effects are measured
Level of Congestion
convenient
comfortable
fast
Travel time
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Case Studies
United States of America
Today, more than 100 TODs exist within the US mainly
around heavy, light and commuter rail stations. (Cervero 1994)
In the United States, 37.4% of TODs surround heavy rail
31.3% light rail
21.8% commuter rail
7.8% bus
1.7% surround ferry transit (Cervero, 2001).
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Case Studies
According to (Dittmar & Poticha, 2004) residents of TOD-like
neighborhoods in the San Francisco Bay Area had almost half
the vehicle miles traveled (VMT) per year.
with exponential population growth such as Charlotte, NC;
Seattle; Denver and Houston have major TOD thus travel time
has reduced(Baldassare, Knight et al. 1979).
Both Charlotte and Houston have new (since 2004) light rail
systems whose ridership have exceeded their projections and as
a result automobile dependence has decreased.
29. Management and Prediction Demand
Case Studies
TODs were encouraged by local transit agencies hence
increased transit Ridership
which in turn reduced greenhouse gas emissions, relieved
congestion, and promoted healthier lifestyles.
study found that TOD improved the effectiveness of transit
investments by 20%-40% (Parsons & Douglas, 1996)
30. Management and Prediction Demand
Case Studies
TOD facilitates economic development and raise revenues for
the agency. (Arrington and Cervaro, 2008)
They achieved the following objectives
Promoted public transport(ridership)
Enhanced livability,
Fostered wider housing choices,
Provided private development opportunities
Reduced parking requirements,
Improved air quality
Promoted intermodal integration.
31. Management and Prediction Demand
Case Studies
Rosslyn-Ballston Redevelopment Corridor
Established in May, 1996.
As of 2004, the corridor had more than 21 million square feet
of office space. Retail and commercial
3,000 hotel rooms and 25,000residences (Parsons & Douglas,
1996).
The corridor covers 2 square miles compared to approximately
14 square miles of a comparable suburban layout.
Between 1991 and 2002, Metro ridership within the corridor
doubled with nearly 50% of residents commuting by transit
32. Management and Prediction Demand
Case Studies
During the planning stages, County officials focused on the
following principles:
Exhibit Compact Building Design
Provide ranges of housing types
Promote “walkable” neighborhoods
Exhibit a distinct sense of place
Preserve open space
33. Management and Prediction Demand
Case Studies
Utilize existing development
Provide transportation choices
Practice fair decision-making
Promote stakeholder participation
In a national survey of 90 transit agencies, nearly half of the
agencies reported having
regional vision, policy, or plan in place that calls for compact
development organized around transit.” (Cervero 2001)
34. Management and Prediction Demand
Case Studies
In San Diego, the density threshold for residential dwellings is
18 per acre
in an urban TOD serving light rail and 12 units per acre in
neighborhood TODs where bus service is the major transit
mode.
In Portland, Oregon,values range from 12 to 30 units for light
rail districts based on the distance to the station
12 to 24 units per acre for bus districts based on distance from
the stop. (Parsons & Douglas 1996)
35. Management and Prediction Demand
Case Studies
Between 1991 and 2002, Metro ridership within the corridor
doubled with nearly 50 % of residents commuting by transit.
Arlington County planners state that when residents are
involved in developing plans they are more supportive of dense
development.
Arlington expanded its density bonus provisions allowing 25
percent more density.
In 2002, the Arlington Corridor was selected by the U.S.
Environmental Protection Agency (EPA) as the recipient of
the National Award.
36. Management and Prediction Demand
Case Studies
Curitiba, Brazil
Curitiba is the capital of Paraná, one of Brazil’s most southern
states.
City planning began nearly three centuries ago when city
leaders first established building regulations
The number of trees that could be cut was limited and
required that homes have roofs made of tile, not wood.
During the second half of the 19th century, Curitiba’s
population tripled due in part to immigrants from Japan,
Lebanon and Syria.
Many of Curitiba’s sister cities experienced high unemployment
rates,impoverished conditions, and congestion.
37. Management and Prediction Demand
Case Studies
From 1950 and 1990, Curitiba experienced high rates of
growth going from 300,000 residents to 2.1 million.
Once an agricultural center, Curitiba became an industrial and
commercial powerhouse. To accommodate this growth.
Curitiba made the decision to plan for the mobility of people
rather than cars.
Giving both pedestrians and mass transit priority over
automobiles in highly congested corridors.
Between 1974 and 1995, the city’s accessibility network
developed dramatically.
38. Management and Prediction Demand
Case Studies
Today, it includes high-capacity buses operating on dedicated
transit ways, express bus service, orbital routes that connect
bus ways,
Curitiba has over 100 feeder lines that run between low-density
neighborhoods and trunk line services.
The network passes through 13 municipalities carrying 2.4
million passengers per day with 34 terminals over 385 lines
(Parsons Brinckerhoff Quade & Douglas, 1996)
Curitiba had the following policies and goals to achieve after
developing TODs
39. Management and Prediction Demand
Case Studies
Transit corridors zoned for mixed-use residential and office
development to guarantee that buildings both produce and
attract trips
Density bonuses that encourage retail shops and restaurants on
the first two floors of all buildings fronting on the transit ways
Areas outside the transit corridors zoned for residential
neighborhoods
Large-scale shopping centers only allowed in transit corridors
Public housing for low-income families built along the transit
ways
40. Management and Prediction Demand
Case Studies
In downtown, a restricted parking supply with a pedestrian
environment emphasized the following
Walkability
Traffic congestion reduction
increased density
more open space
private funding support
job creation
intense community involvement were all a part of vision or goal
.
41. Management and Prediction Demand
Case Studies
Emery Station, Emeryville
The Emery Station has 20-acres of mixed-use development in
the East Bay area.
Initiated by Amtrak, construction of the rail station
In 1998 as a result of negotiations between the City of
Emeryville and Chevron who previously owned the land then it
started .
Anchored by an Amtrak station that makes 13 daily round
trips,
The TOD currently includes 550,000 square feet of office and
150 residential units and ground-floor retail.
Residential units consist of lofts, town homes and senior
housing.
42. Management and Prediction Demand
Case Studies
More than $200 million invested in the station
The City also completed pedestrian bridge over the Amtrak
tracks to a nearby mixed-use center.
BART station is two miles away, the City of Emeryville saw fit
to provide its residents and businesses with access to BART.
shuttle bus that connects the development to the McArthur
BART Station operating from 5:45 a.m. to 9:30 p.m. every 15
minutes.
Figure 2.2 and Figure 2.3 are before and after photos of the
Emery Station development.
43. Management and Prediction Demand
Case Studies
Emery Station before development
Figure 1 Emery Station before development
44. Management and Prediction Demand
Case Studies
Emery Station after development
Figure 2 Emery Station after development
45. Management and Prediction Demand
Case Studies
Kelvin Grove Urban Village(KGUV)
Located in Brisbane Australia
Designed as suitable and mixed use development
Brisbane Metropolitan area has a population of approximately
1.9m
KGUV spans over 16.57 Ha of land area
The mixed use development consists of educational,
residential, commercial, recreational, retail and office land use.
KGUV is an educational based mixed use development
46. Management and Prediction Demand
Case Studies
Mixed land uses at KGUV
Table 1 showing mixed land uses at KGUV
47. Management and Prediction Demand
Case Studies
Transport facilities at KGUV
KGUV is well connected to arterial roads
Has an internal street network forming grid patterns with parks
and open spaces
It has side walks on both sides of all streets and through parks
and cycle lanes.
This encourages,support walking and cycling
Number of car spaces restricted to one space per 30m2 for all
non residential development.
Rstricted parking facilities to discourage drivers from driving
their cars
Promote the use of suitable modes of public transport like
walking, cycling and use of public transport
48. Management and Prediction Demand
Case Studies
Aerial overview of KGUV
Figure 3 Aerial overview of KGUV
49. Management and Prediction Demand
Case Studies
Figure1 shows an overview of KGUV the public transport
corridors and its proximate transit stops.
Yellow lines show the transport corridors
Blue symbols indicate the location of the bus stops or bus way
stations catering for KGUV users.
KGUV is served by 16 bus services including 9 express and very
high frequency services.
50. Management and Prediction Demand
Case Studies
In conclusion, TOD has reduced traffic congestion,increased
Ridership, increased the quality of life and encourages bicycling and
walking further more government and TOD agencies has earned
revenue if form of conducting economical business like
shops,recreation centers,rentals and house and land value.
Therefore it would be recommended that countries that have not
yet implemented TODS to plan and implement them for the
betterment of traffic congestion reduction.
52. Management and Prediction Demand
References
Baldassare, M., R. Knight, and S. Swan (1979), Urban Service
and Environmental Stressor:The Impact of the Bay Area Rapid
Transit System on Residential Mobility.Environment and
Behavior. 11(4): p. 435-450.
Boarnet, M. G., & Compin, N. S. (1999). Transit-oriented
development in San Diego County: the incremental
implementation of a planning idea. Journal of the American
Planning Association, 65(1), 80-95.
Cervero, R., & Kockelman, K. (1997). Travel demand and the
3Ds: density, diversity, and design. Transportation Research
Part D: Transport and Environment, 2(3), 199-219.
Cervero, R.(2001), Transit-Oriented Development in the
United States: Experiences,Challenges, and Prospects, in
Transit Cooperative Research Program Report 102.
53. Management and Prediction Demand
References
Cervero, R., & Day, J. (2008). Sub urbanization &
transit-oriented development in China.Transport Policy,15(5),
315-323.
Dittmar, H., & Poticha, S. (2004). Defining transit-oriented
development: The new regional building block. The new
transit town: Best practices in transit-oriented development,
20-55.
McNulty, S. A., Porter, W. F., Mathews, N. E., & Hill, J. A.
(1997). Localized management for reducing white-tailed deer
populations. Wildlife Society Bulletin, 265-271.
54. Management and Prediction Demand
References
Newman, P. W., & Kenworthy, J. R. (1988). The transport
energy trade-off: fuel-efficient traffic versus fuel-efficient cities.
Transportation Research Part A: General, 22(3), 163-174.
Parsons Brinckerhoff Quade & Douglas (1996), I., Public
Policy and Transit-Oriented Development: Six International
Case Studies, in Transit Cooperative Research Program Report
16, Transportation Research Board. p. 1-173.
Weisbrod, G., Vary, D., & Treyz, G. (2003). Measuring
economic costs of urban traffic congestion to business.
Transportation Research Record: Journal of the
Transportation Research Board, (1839), 98-106.