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Similar a Theme 7 Broader interactions, public transportation and city form (20)
Theme 7 Broader interactions, public transportation and city form
- 1. © P. Christopher Zegras 9/24/2013
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Broader Interactions: Public
Transportation and City Form
Bus Rapid Transit (BRT) Workshop:
Experiences and Challenges
20 September 2013
Professor Christopher Zegras
Department of Urban Studies & Planning
Massachusetts Institute of Technology
1
Download this .ppt
• http://web.mit.edu/czegras/Public/
• And/or email me: czegras@mit.edu
2
- 2. © P. Christopher Zegras 9/24/2013
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Content
• Built Environment (BE) = f (Transport) and
Transport = f (BE)
– Background and basic theory
• Transport = f (BE)
– theory, evidence, policy implications.
• BE = f (Transport)
– theory, evidence, policy implications.
• Conclusions and Questions
3
Land Use-Transport Interaction:
Theoretical Framework
Land Use
Land Uses (Activities)
Land, Floor Space
Prices Demand
Transportation
Travel (Activities)
Transportation System
Time
Costs
Demand
Connectivity
Spatial
Distribution
Accessibility 4
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Built Environment and Public
Transport: The Promise
• Public transport changes the spatial
economy of place
– Accessibility benefits/costs reflected in land
prices (Zegras et al., 2013)
– Agglomeration economy potentials
• Expanded labor markets
• Job concentration and reduced costs of inputs and
knowledge spillovers
(Chatman and Noland, 2013)
5
Built Environment and Public
Transport: The Promise
• Developers: Higher profits
– Higher densities possible
– Higher price/unit possible
• Users: Higher benefits
– Expanded accessibility
– Lower costs (?)
– Higher quality of life/well-being (Cao, 2013)
• Politicians: More desirable places
– Happier voters
6
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The Broader Context
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
—
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Population(Millions)
“Less Developed”
Urban
“Developed” Urban
Total World
Source: United Nations, Department of Economic and Social Affairs (DESA)
7
% Change Population by Census Tract (2000-10)
US
Census
2012
8
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Paris
Angel et al, 2011
9
Bandung,
Indonesia
Angel et al, 2011
10
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Average Tract Density: 20 US Metro Areas
Angel et al., 2011
11
World “Suburbanization” Trends
Angel et al., 2011 12
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Transport = f (LU)?
Something new?
Meyer, et al, 1965 (from Kain, 1999)
Howard’s “Garden City”
13
14
The Built Environment and Mobility: A
Question of Scale
Scale Refers To Built Environment
Concepts/Indicators
Metropolitan Urban Structure Overall City Size,
population, gross density,
“skeletal” forms (e.g, radial)
Intra-
Metropolitan
(meso)
Urban Form Dispersion, concentration,
mixes, grain, access
networks
Micro Scale:
(neighborhood)
Urban Design “Internal Texture”, Density,
Mixes of Uses, Street
Networks, etc.
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Urban Density (persons/hectare)
15,000
10,000
5,000
100 200 300 400
PerCapitaCarKms
Hong Kong
Sacramento, CA
?
?
xSantiago
13 US Cities
7 Canadian Cities
3 Wealthy Asian Cities
11 European Cities
6 “Developing” Asian Cities
6 Australian Cities
Urban Density (persons/hectare)
15,000
10,000
5,000
100 200 300 400
PerCapitaCarKms
Hong Kong
Sacramento, CA
?
?
xSantiago
13 US Cities
7 Canadian Cities
3 Wealthy Asian Cities
11 European Cities
6 “Developing” Asian Cities
6 Australian Cities
Kenworthy & Laube, 1999.
Newman & Kenworthy…
15
Ingram, 1998, p. 1027.
Newman & Kenworthy…
16
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Macro-
Scale
Form &
Function
Bertaud, 2004
17
18
Micro Scale Built Environment
Crane, 1996
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19
Formalizing the Theoretical
Framework
20
Crane’s Trip-Based (Time/Cost-Based)
Framework
Crane, 1996
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21
A Trip-Based (Cost-Based)
Framework
Auto Travel
Demand
Indicator
Grid Street
(shorter trips)
Traffic
Calming
(slower trips)
Mixed Uses &
Densification
(one trip, more
purposes,
slower speed
All Three
Car Trips
Increase (for
all modes,
likely)
Decrease
Increase or
Decrease
Increase or
Decrease
Vehicle Miles
Traveled
(VMT)
Increase or
Decrease
Decrease
Increase or
Decrease
Increase or
Decrease
Car Mode
Choice
Increase or
Decrease
Decrease
Increase or
Decrease
Increase or
Decrease
Crane, 1996
22
To Better Understand Possible
Effects…
We need to know
• Elasticities of trip demand with respect to
speed and distance
• Cross-elasticities among modes
– How changes for one mode (eg in distance)
affects demand for other modes
• Differentiate by trip purpose
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Net Utility Approach
• Extending beyond Crane…
• The Built Environment influences disutility
and utility
Maat et al, 2005
23
Stylized Effects of Travel Time
Changes
Maat et al, 2005
24
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Stylized Effects of Mode Changes
Maat et al, 2005
25
26
Net Utility Framework
• Land uses influence net utility:
– Positive utility = activity realization
– Negative utility (disutility) = travel cost
• Extends beyond Crane
– Reveals a dual ambiguity of land use’s influences
• Uncertain influence on trip costs (disutility), thus travel
• Uncertain influence on activities (utility), thus travel
• What happens with saved time?
A. Invest in going to higher utility destinations
B. Carry out more activities
C. Dedicate more time per activity
– Travel demand increases with?
– A and B
– Consistent with…. constant travel time budgets (e.g., Schafer, 2000).
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TB = f (BE)?
Empirical Challenges: Unclear
pathways of effects
Transport-Efficient
Neighborhood
Transport-Efficient
Behavior
Transport-Efficient
Preferences
Spatial cognition, etc…
27
A “Macro-Level” Example
Netherlands
Policy Land Use Behavior
(Schawen et al, 2004)
28
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National-Level Planning Policies
Netherlands
• 1970s-1980s
– “concentrated decentralization”
• 1980s
– “compact urban growth”
– with urban renewal subsidies
• 1990s
– “A-B-C location policy”
• A: centrally located sites
• B: outside CBDs, but still public transport connected
• C: highway-oriented sites
• Challenge: growth in service/office sector
• Retail policy
• Overall: mixed success
– Primarily guiding residential and retail development
29
Schwanen et al, 2004.30
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Netherlands: Estimated Effects?
• Data
– Travel
• One-day travel survey (NTS)
• Male/female Head of Household
– Land Uses
• Macro: urban structure (mono-, poly-centric)
• Meso: degree of urbanization
• Travel Effects
– Mode Choice
– Distance and time
Schwanen et al, 2004.31
Netherlands: Conclusions & Recs
Schwanen et al, 2004.32
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“Micro-Scale” Effects
Meta-Analysis, Case Study
(Jinan)
33
Meta-Analysis: Elasticities of
Walking with respect to BE
Ewing and Cervero, 2010.
34
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Meta-Analysis: Elasticities of
Transit Use with respect to BE
Ewing and Cervero, 2010.
35
Micro-level Example: BE and BRT Pedestrian
Catchment Area (PCA) in Jinan China
(Jiang et al, 2012)
36
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Arterial- Edge Corridor
(Jingshi St.)
1
(Jiang 2010)
37
Integrated- Boulevard Corridor
(Lishan Rd.)
2
(Jiang 2010)
38
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Below- Expressway Corridor
(Beiyuan St.)
3
(Jiang 2010)
39
Approach
, , , ;
• Station area user survey
• Built Environment Analysis
• Regression
40
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CORRIDOR WALKABILITY
A BRT Users’ Perspective
29%
33% 33%
26% 26% 28%
18%
24% 26%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Crossing is safe. Crossing is easy. Walking on sidewalks
is safe.
Arterial-edge
(n=464)
Integrated-boulevard
(n=356)
Below-expressway
(n=946)
41
Unsafe crossing, poor signals…
(Jiang 2010)
42
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Distance… (Jiang 2010)
43
(Jiang 2010)
44
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CORRIDOR WALKABILITY
A BRT Users’ Perspective
69%
47% 45%
50%
33%
24%
38%
35%
27%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pavement is good. Streets are clean. Few blockages are on
sidewalks.
Arterial-edge
(n=464)
Integrated-boulevard
(n=356)
Below-expressway
(n=946)
45
CORRIDOR WALKABILITY
A BRT Users’ Perspective
48%
42%
70%
58%
39%
49%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trees on sidewalks make
walking comfortable.
Facilities along streets
meet my demand.
Arterial-edge
(n=464)
Integrated-boulevard
(n=356)
Below-expressway
(n=946)
46
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Walk next to trees…
Arterial-Edge Corridor
47
(Jiang 2010)
Walk under trees…
Integrated-Boulevard Corridor
48
(Jiang 2010)
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Walk without trees…
Below-Expressway Corridor 49
(Jiang 2010)
475
647
582
329
501
459
0
100
200
300
400
500
600
700
Avg Walking Distance
Avg Straight-line Distance
(m)
Detour
Factor 1.59 1.36 1.33
CORRIDOR WALKABILITY
Directness
Walking
distance
Straight-line
distance
50
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26
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0
150
300
450
600
750
900
1050
1200
1350
1500
1650
1800
1950
2100
2250
2400
2550
2700
2850
3000
3150
3300
3450
3600
3750
3900
Percentage of BRT riders
Access/Egress Walking Distance (m)
Terminal Station
Transfer Station
Typical Station
Station Function vs. Access/Egress Walking Distance
Walking Distance (m) Typical Station Transfer Station Terminal Station
Mean 547 587 1365
Median 435 458 1311
Maximum 2738 2067 5114
51
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0
150
300
450
600
750
900
1050
1200
1350
1500
1650
1800
1950
2100
2250
2400
2550
2700
2850
3000
3150
3300
3450
3600
3750
3900
Percentage of BRT riders
Access/Egress Walking Distance (m)
Arterial‐Edge
Integrated‐Boulevard
Below‐Expressway
Corridor Type vs. Access/Egress Walking Distance
(non-terminal stations only)
Walking Distance (m) Arterial‐Edge Integrated‐Boulevard Below‐Expressway
Mean 475 649 580
Median 412 520 458
Maximum 1635 2023 2738
52
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Potentially confounding factors
Trip Maker
• Age
• Gender
• Car Ownership
• Household Income
• Occupation
• Frequent BRT User or not
Trip
• Purpose
• Time
• Alternative Mode Availability
• In Group or not
System
• Level of Service
• Transit Fare
Station Context
• Station Function (terminal, transfer?)
• Distance to City Center
• Density Gradient
• Connectivity (Feeder road length)
• Level of Feeder-bus Service
No need control because BRT riders are granted free transfer
between BRT lines and thus using the same system per se.
53
Catchment Area Density Gradient: Hill/ Valley/ Flat
Hill Pattern (convex) Valley Pattern (concave)
BRT
BRT
Station 3 Station 8
STATION CONTEXT
Source: http://jinan.edushi.com/
54
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E(Walk Distance)
= 600
+ 150 *(Integrated_Boulevard_Corridor)
+ 400 *(Terminal_Station)
- 100 *(Transfer_Station)
- 150 *(Density_Hill)
+ 150 *(Density_Valley)
+ 50 *(Distance_to_Center in km)
Radial Distance Guidelines for Pedestrian Zones around
BRT Stations AND RRT Stations
Radial Distance (meters)
Corridor Type Terminal Station Non‐terminal Station
BRT Arterial‐Edge 600‐1000 300‐600
BRT Integrated‐Boulevard 1000‐1500 600‐1000
BRT Below‐Express 800‐1200 400‐800
RRT Underground 1200 700‐900
RRT Elevated 1300 800‐1000
Jiang et al, 2012; Zhao & Deng, 2013
E(Walk Distance)
= 900*(Underground typical sta.)
+ 300 *(Terminal_Station)
+ 100 *(Elevated Station)
- 100 *(if Transfer station)
+ 10 *(Distance_to_Center in km)
55
E(Walk Distance)
= 600
+ 150 *(Integrated_Boulevard_Corridor)
+ 400 *(Terminal_Station)
- 100 *(Transfer_Station)
- 150 *(Density_Hill)
+ 150 *(Density_Valley)
+ 50 *(Distance_to_Center in km)
Radial Distance Guidelines for Pedestrian Zones around
BRT Stations AND RRT Stations
Radial Distance (meters)
Corridor Type Terminal Station Non‐terminal Station
BRT Arterial‐Edge 600‐1000 300‐600
BRT Integrated‐Boulevard 1000‐1500 600‐1000
BRT Below‐Express 800‐1200 400‐800
RRT Underground 1200 700‐900
RRT Elevated 1300 800‐1000
Jiang et al, 2012; Zhao & Deng, 2013
E(Walk Distance)
= 900*(Underground typical sta.)
+ 300 *(Terminal_Station)
+ 100 *(Elevated Station)
- 100 *(if Transfer station)
+ 10 *(Distance_to_Center in km)
56
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29
Terminal station presents a unique opportunity
for large transit-oriented development…
RECOMMENDATIONS
(Jiang 2010)
57
This probably will NOT work…
(Jiang 2010)
RECOMMENDATIONS
58
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30
Make crossing safer…
(Jiang 2010)
59
Put more trees and stores along the sidewalk
in an appropriate way…
(Jiang 2010)
60
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31
Jinan: Key Takeaways
• BRT Operators should be encouraged to
push for designs that increase their PCA
• That, in turn, may further influence urban
development possibilities…..
61
Land Use = f (Transport)?
Muller, 2004
62
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32
Rail Transit Effects
(Baum-Snow & Kahn, 2000; See Appendix 1)
Aims
1. How new rail transit attracts commute
trips to transit
2. Which demographic groups benefit most
from rail improvements
3. Rail transit influence on land values
63
Possible Rail Transit Effects
• Existing Residents Switch to Rail
• New Residents Move into Transit Tracts
• Property Values Increase
64
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33
Results: Transit Use
• There is some Tiebout migration of transit users
to tracts
– i.e., “self-selection”
– Migration rates are higher in tracts with increased
transit access
• Induced transit-oriented development
• Also, transit-shifting by existing residents
– In fact, most mode shift due to this effect
• Overall effects…
– Small 1.4% increase in transit with a 2 km decrease
in distance to transit (from 3 to 1 km)
65
Results: Transit Capitalization &
User Groups
• 3 km to 1 km decrease in transit distance
increases rents by $19/month, house
value by $5,000
– More gain in travel time savings: $1,200/year
• College educated and home-owners more
likely to be in census tracts closer to
transit
66
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34
More recent analysis (USA)
• Bus+rail services [seats per capita] -
together and almost equally - increase
downtown employment
• Downtown wages increase
• Metropolitan area productivity increases
67
Chatman, 2013
How to “get” TOD?
Land policies of relevance
• parking restrictions
• land assembly
• high-density zoning
And, proper corridor alignment…
And, proper economic environment
• Growth, demand for density
Handy, 2005 68
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35
Would Bus Rapid Transit
(BRT) Effects and Needs be
the Same?
69
Back to Theoretical Impacts
Users
• Revealed Preference (Washington, DC)
• Local bus, express bus, commuter rail, metro in
Washington, DC
• Stated Preference (Boston)
• Bus, light rail in Boston
“rail and bus services which provide similar
service attributes have the same ridership
attraction”
Ben-Akiva and Morikawa, 2002
70
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Back to Theoretical Impacts
User
• In New Jersey, USA: LRT
– It’s the form, not the rail
– In fact, regular bus, stronger behavioral
effects than rail, after form-controls
• better bus service relaxation of parking,
zoning & other development restrictions
key
Chatman, 2013
71
Back to Theoretical Impacts
• Developers (24 interviews in Minnesota)
– Transit (bus and rail) = secondary benefit
– Bus and rail both seen positively
– Bus transit referenced “slightly more often
than” LRT and TOD
– Conventional bus neighborhoods often
mentioned
• “employers focus more on current transit options in
site selection than on proposed future options.”
72Fan and Guthrie, 2013
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37
Developer Perceptions
• Los Angeles
Sustainable Transit
Communities
Scorecard, 2011
– 13 BRT + 36 Rail sites
– Orange Line BRT sites
“development potential”
ranked 3, 8, 12, 19, and
20
– BRT sites’ overall
rankings lower due to
suburban character and
lack of walkability
More info at:
http://www.compassblueprint.org/Documents/CBResources/LA_Sustainable_Transit_C
ommunities_Scorecard.pdf.
73
BRTOD Strengths and
Weaknesses
Strengths
• Speed and cost of
implementation
• Flexibility, adaptability,
extendability
Weaknesses
Judy, 2007
74
• Poor image of buses
• Little technical knowledge
and empirical evidence
• Real externalities (noise,
AQ)
• Perceived externalities
(noise, AQ, crime)
• Perceived (real?)
impermanence
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38
BRTOD
Empirical Evidence
75
Curitiba: BRTOD “poster child”
(See Appendix 2)
Land Use-Transportation Integration from
Beginning: A “Linear City”:
• Promote densification of land uses on axes
– Zoning, Regulations, Incentives
• Focusing urban expansion along structural axes
– Centered on busways
76
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39
Transmilenio
(Rodriguez and Targa, 2004; see
Appendix 3)
77
~Current Network
114 Stations; 84 Kms; 1263 vehicles; 27 km/h; 200K peak hour passengers
83 Feeder routes; 516 feeder buses
78
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40
Hidalgo, 2006.
Calle 13 – Av. Caracas
79
Vehicles
Graftieaux, 2005.
80
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41
Stations
Graftieaux, 2005.
81
1.5 km
buffer
82
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42
Results
• Elasticity of rent with
respect to BRT stop dist.
– -0.16 to -0.22
• Every five minutes from
BRT stop, rent declines by
US$15
• Elasticity of rent with
respect to BRT Corridor
– 0.19 to 0.21
• Every 100 meters from
corridor, rent goes up by
US$77 83
Comparing Results
• Results (in terms of % change in property value)
fairly comparable to
– Los Angeles Blue Line
– DC WMATA
• Slightly lower than San Diego (LRT) and UK
Tramlink (Manchester)
• Estimated absolute premium (annualizing rents)
– US$440-650 per 100 meters
– Roughly Double the Baum-Snow & Kahn Effect
(measured from 3 to 1 km change)
84
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43
Other Notes and Commentary
• No apparent Regional Accessibility Benefit
• Short time frame of analysis may mean
conservative estimate
• Cross-sectional analysis
• Corridor effect might be confounded
– By other traffic
• But, station effects might also be confounded
– E.g., urban recovery
• Residential land only
85
Urban Recovery
Hidalgo, 2006.
86
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44
Commercial Development
Hidalgo, 2006.
87
Commercial Development
Hidalgo, 2006.
88
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45
Increasing # of BRT “land” value studies
• Seoul (Cervero and Kang, 2009)
– Residential: 5-10% premium within 300 meters
of BRT stop
– Non-residential: 3-26% premium within 150
meters of BRT stop
• Pittsburgh (Perk and Catalá, 2009)
– Residential properties: $60/meter at 30 meters;
$6/m at 300 meters
• Boston condo sales (Perk, et al., 2013)
– Immediate drop, then increase, 7.6% premium
89
Seoul’s BRT Amenity
Cervero and Kang, 2009
90
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46
Canoga Orange Line Station
(LA)
91
Canoga Orange Line Station
92
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47
Getting to BRTOD
• Transit Service
– Interconnectedness
– Station/route location/alignment
– Public investment in transit system
• Area Design/Development
– “Right” development policies
– Station-area walkability
– Public investment in station areas
• Institutionality
– Regional planning/ coordination
– Integrated land use-transit decision-making
93
Judy, 2007
94
Transit = f (BE): Summary
• Consider the geographical scale of analysis/intervention
– Generally, theory implies same types of effects, operating at
different scales
• Theoretically, impacts are ambiguous
• Complexity of LUT relationships increases with society’s
complexities
– Time routines, age, family cycle, etc.
– Keep in mind the type of potential activities (e.g., trip purpose) and
related spatial and temporal constraints
• Simple consideration: BE influence on walk influence to
station access
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48
BE = f (Transit): In Summary
• Public Transit and BRT, in right conditions, will
influence urban form
• Land Value effects are consistently seen
• Institutional barriers to land value capture (LVC)
– Including poor transport finance pictures
• LVC not a panacea
– Realistic amount to raise, will be modest, in most cases
– Ex-ante system in place (before build/expand)
• Need to better understand BRT’s particular urban
design challenges/opportunities
– (see PUC-MIT BRT Corridor Design Workshop)
95
BRT Design Workshop
Image courtesy of Team 2, Assn3 (18 Sept, 2013):
Soledad Guerrero, Amalia Holub, Markus Niehaus, Sue
Pot, Dany Ríos, Anson Stewart 96
- 49. © P. Christopher Zegras 9/24/2013
49
Acknowledgments
You: For listening
Anson Stewart: for research
contributions
97
Appendix 1
Baum-Snow and Kahn
98
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50
Approach
• Case Studies
– Expansions
• Boston, Chicago
– Comprehensive New Networks
• Atlanta, Washington, DC
– Incremental Expansion
• Portland, OR
99
Data
• Census Tract Data
• Public Use Microdata Sample (PUMS)
– 1% sample, micro data
• Constructed Transit Coverages to
represent system changes (1980-1990)
– Show declines in mean tract distance from
transit (all cities): 5 km to 3 km
100
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51
Analytical Approach
• Transit Use: 3 models
1. Use = f (Tract Distance)
2. Change in use = f (Change in Tract Distance)
3. Change in use = f (Change in Tract Distance,
Migration)
• Transit Capitalization
– “Hedonic” home price capitalization
– Change in home price = f (change in distance)
• Transit Beneficiaries
– Change in Distance to Transit = f (demographics)
101
Relative Suburban Benefits from
Rail Transit
Baum-Snow & Kahn, 2005.
PublicTransitUsebyDecadefor16Cities
thatExpandedRailTransit(1970-2000)
102
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52
Some Problems with Baum-Snow & Kahn
• City fixed effects
– Transit markets/service very local
• Ignore other investments/policies occurring at
same time
– E.g., highway investments
– And their expansionary effects
• Rail transit almost certainly retains central city
vitality
– Not captured in their model
– No employment effects captured in model
• Commute trips only
• Possible issues with using census tract…
See, e.g., Voith, 2005.
103
Appendix 2
Details on Curitiba’s Land Use
Policies
104
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53
Land Use Policies
• Zoning Regulations within 2-blocks of
structural arteries
– Residential FAR: up to 4
– Office FAR: up to 5
– Directly abutting buildings: First two floors can
extend directly to property lines
– At least 50% of ground and second floors
must be commercial-retail
• Not counted towards FARs
– Above 2nd Floor: 5 meter setback required
Cervero, 1998.
105
Land Use Policies
• Transferable Development Rights (TDRs)
– Within Curitiba Historic Area
• Transit-Supportive Housing Policies
– Direct community-assisted housing towards
transportation corridors
– Additional residential density permitted with
contributions to low-income housing fund
• Contributions = 75% of market value of add’l area
• Only allowed in residential zones within walking
distance of busways
Cervero, 1998.
106
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54
Residential Densities Along Structural Axes
and Adjoining Neighborhoods
TCRP, 2003.
107
Appendix 3
Transmilenio apartment rent price
effects
108
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55
Transmilenio BRT: Land Effects?
• Estimate Effects on Property Values
– Hedonic Model
• Rental Properties
– Feb-Apr, 2002
– Field visits and newspaper adds
– All properties for rent
– 494 multifamily residential properties
• Dependent variable
– Asking price
• Influencing variables (of interest)
– Accessibility (local and regional)
109
Accessibility: How Measured?
• Local
– Shortest walking time on road network from
location of each property to closest BRT
• Regional
– Line-haul travel time from closest BRT station to
Financial District
– Line-haul travel time from closest BRT station to
Financial District Downtown
– Weighted index of travel time to all BRT stations
• Weighted by the number of passengers travelling
between each pairs
110
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Other Variables
• Proximity effects
– Straight line distance to corridor
– To capture possible negative externalities
• Control variables
– Apartment: Size, # bedrooms, age, etc.
– Location: buffer with spatial average of zone
attributes
• Crime, socioeconomic, demographic, land uses,
etc.
111
Appendix 4
Transit Land Value Capture
An Example Policy Implication
(rail-based) in Chicago USA
112
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57
Chicago: Hedonic Model, CTA
Station Access
p = f (I, N, T)
where:
p is the property sales price;
I is a vector of attributes of the improvements on the parcel, such as number of bathrooms, number
of floors, and age, etc.;
N is a vector of attributes of the neighborhood, such as quality of public facilities and services
(including schools) and socioeconomic characteristics; and,
T is a combined vector of attributes of the transportation-related locational accessibility of the
parcel, such as proximity to transportation services (including transit), relative accessibility to
opportunities across the broader metropolitan area, etc.
Zegras et al. 2013a,
113
Zegras et al. 2013a,
114
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Zegras et al. 2013a,
115
Variation in Elasticity of Property Value with
Respect to Walking Time Based on Properties’
Walk Times to CTA Station
Zegras et al. 2013a,
116
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Land-Based Finance Mechanisms
Derived from Lari et al, 2009
117
Rail Transit Value Capture
Potential: Chicago, Lisbon
Zegras et al 2013b118
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References
• Angel, S., J. Parent, D. Civco, A. Blei (2011) Making Room for a Planet of Cities, Policy Focus
Report, Lincoln Institute of Land Policy.
• Baum-Snow, N. and M. Kahn (2000) The effects of new public projects to expand urban rail
transit. Journal of Public Economics, Vol. 77, pp. 241-263.
• Ben-Akiva, M. and T. Morikawa (2002) Comparing Ridership Attraction of Rail and Bus. Transport
Policy 9 (2) (April), pp. 107–116. doi:10.1016/S0967-070X(02)00009-4.
• Bertaud, A. (2004) The spatial organization of cities: Deliberate outcome or unforeseen
consequence? May: http://alain-
bertaud.com/images/AB_The_spatial_organization_of_cities_Version_3.pdf
• Blackman, A. (2002) Testing the Rhetoric. Regulation (Spring): 34-38.
• Cao, J. (2013) The association between light rail transit and satisfactions with travel and life:
evidence from Twin Cities. Transportation, 40, 921-933.
• Cervero, R. (1998). The Transit Metropolis: A Global Inquiry. Island Press.
• Cervero, Robert, and Chang Deok Kang. “Bus Rapid Transit Impacts on Land Uses and Land
Values in Seoul, Korea.” UC Berkeley Center for Future Urban Transport: A Volvo Center of
Excellence, July 2009. http://escholarship.org/uc/item/4px4n55x
• Chatman, D. and R. Noland (2013) Transit Service, Physical Agglomeration and Productivity in
US Metropolitan Areas. Urban Studies (forthcoming).
• Chatman, D. (2013) Does TOD need the T? On the importance of factors other than rail access.
• Journal of the American Planning Association, 79 (1), pp. 17-31.
• Crane, R. (1996) On form versus function: Will the new urbanism reduce traffic, or increase it?
Journal of Planning Education and Research, Vol. 15, pp. 117-126.
• Ewing, R, R. Cervero (2010) Travel and the Built Environment. Journal of the American Planning
Association, 76(3), pp. 265-294.
119
References (cont’d)
• Fan, Y. and A. Guthrie (2013) Achieving System-Level, Transit-Oriented Jobs-Housing Balance:
Perspectives of Twin Cities Developers and Business Leaders. UMinn CTS 13-24:
http://www.cts.umn.edu/Publications/ResearchReports/reportdetail.html?id=2300
• Geurs, K.T. and B. van Wee (2004) Accessibility Evaluation of Land-Use and Transport
Strategies: Review and Research Directions. Journal of Transport Geography Vol. 12: 127-140.
• IBI Group. 2000. Greenhouse Gas Emissions from Urban Travel: Tool for Evaluating
Neighborhood Sustainability. Healthy Housing and Communities Series Research Report,
prepared for Canada Mortgage and Housing Corporation and Natural Resources Canada,
February.
• Graftieux, P. (2005). World Bank, Personal communication.
• Handy, Susan. (2005) Smart Growth and the Transportation - Land Use Connection: What does
the research tell us? International Regional Science Review 28, pp. 146-167.
• Hidalgo, D. (2006). EMBARQ, Personal communication.
• Ingram, G. (1998) Patterns of Metropolitan Development: What Have We Learned? Urban
Studies, Vol. 35, No. 7, June, pp. 1019-1035.
• Jiang, Y. (2010). CSTC, personal communication.
• Jiang, Y., C. Zegras, Mehndiratta, S. (2012). Walk the line: station context, corridor type and bus
rapid transit walk access in Jinan, China.” Journal of Transport Geography, 20(1), 1–14.
• Judy, M. (2007). The Potential for Bus Rapid Transit to Promote Transit Oriented Development:
An Analysis of BRTOD in Ottawa, Brisbane, and Pittsburgh. MCP Thesis, MIT:
http://hdl.handle.net/1721.1/40122
• Kain, J. (1999) The Urban Transportation Problem: A Reexamination and Update. Essays in
Transportation Economics and Policy. Brookings.
120
- 61. © P. Christopher Zegras 9/24/2013
61
References (cont’d)
• Kenworthy, P. and F. Laube (1999) Patterns of automobile dependence in cities: an international
overview of key physical and economic dimensions with some implications for urban policy.
Transportation Research A, Vol. 33, pp. 691-723.
• Lari, A., Levinson, D., Zhao, Z., Iacono, M., Aultman, S. Das, K.V., Junge, J., Larson, K.,
Scharenbroich, M. (2009) Value Capture for Transportation Finance: Technical Research Report.
Minneapolis: The Center for Transportation Studies, University of Minnesota
• Maat, K., B. van Wee, D. Stead (2005) Land use and travel behaviour: expected effects from the
perspective of utility theory and activity-based theories. Environment and Planning B: Planning
and Design, Vol. 32, pp. 33-46.
• McNally, M. and A. Kulkarni. (1997) Assessment of Influence of Land Use-Transportation System
on Travel Behavior. Transportation Research Record 1607, pp. 105-115.
• Muller, Peter O. Transportation and Urban Form: Stages in the Spatial Evolution of the American
Metropolis. Chapter 3 in The Geography of Urban Transportation, 59-85. S. Hanson, ed. 3rd
edition, Guildford Press, 2004
• Perk, V. and M. Catalá (2009) Land Use Impacts of Bus Rapid Transit: Effects of Station Proximity
on Property Values of Single Family Homes Along Pittsburgh’s Martin Luther King, Jr., East
Busway, National Bus Rapid Transit Institute, FTA Report FTA-FL-26-7109.2009:
http://www.nbrti.org/docs/pdf/Property%20Value%20Impacts%20of%20BRT_NBRTI.pdf
• Perk, Victoria, Steven Bovino, et al. (2013) Impacts of Boston’s Silver Line Bus Rapid Transit
(BRT) on Sale Prices of Condominiums Along Washington Street. 92nd Annual Meeting of the
Transportation Research Board, Washington D.C., January.
121
References (cont’d)
• Rodríguez, D. and Targa, F. (2004) Value of Accessibility to Bogotá’s Bus Rapid Transit System.
Transport Reviews, Vol. 24, No. 5 (September): 587-610.
• Schwanen, T., Dijst, M. and Dieleman, F. (2004) Policies for Urban Form and their Impact on
Travel: The Netherlands Experience. Urban Studies Vol. 41, No. 3: 579-603.
• TCRP (2003) Bus Rapid Transit Volume 1: Case Studies in Bus Rapid Transit. TCRP Report 90:
http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp90v1_cs/Curitiba.pdf
• US Census Bureau (2012) Patterns of Metropolitan and Micropolitan Population Change: 2000 to
2010, Census Special Reports, September.
• Voith, R. (2005) Comment on Effects of Urban Rail Transit Expansions: Evidence from Sixteen
Cities, 1970–2000 (Baum-Snow and Kahn). Brookings-Wharton Papers on Urban Affairs: 198-
206.
• Zegras, C., S. Jiang, C. Grillo (2013a) Sustaining Mass Transit through Land Value Taxation?
Prospects for Chicago, Draft Paper prepared for Lincoln Institute of Land Policy:
http://web.mit.edu/czegras/www/Zegras%20et%20al_LVT%20and%20CTA.pdf
• Zegras, C., S. Jiang, C. Grillo, L. Martinez (2013b) Capture the Value to Finance Transit
Systems? A Comparative Assessment of Chicago and Lisbon, Draft.
• Zhang, M. (2004) The Role of Land Use in Travel Mode Choice: Evidence from Boston and Hong
Kong. Journal of the American Planning Association, Vol. 70, No. 3, Summer, pp. 344-360.
• Zhao, J. and Deng, W. (2013) Relationship of Walk Access Distance to Rapid Rail Transit
Stations with Personal Characteristics and Station Context. Journal of Urban Planning and
Development (forthcoming).
122