www.TransformingTransportation.org

Examining the Relationship

between Bus Rapid Transit (BRT) and

the Built Environment in Latin America

Erik Vergel-TovarPhD Candidate, UNC-Chapel Hill, and 2014 Lee Schipper Memorial

Scholar

Presented at Transforming Transportation 2015

Examining the relationship between Bus Rapid Transit (BRT) and the built

environment in Latin America

C. Guatemala

Bogotá

Quito

Guayaquil

Goiânia

Sao Paulo

Curitiba

Erik Vergel-Tovarevergel@live.unc.edu

PhD Candidate and Lee Schipper ScholarDepartment of City and Regional Planning

University of North Carolina at Chapel Hill

© IPPUC (2011)

7 cities4,837,631 # passengers per day

15.42 % of world ridership

Motivation

Conventional wisdom and some

rail-based evidence about

transit-oriented development

(TOD) suggest:

• there is a positive association

between transit ridership and

population density around stops

BRT trunk corridors and population density in

Curitiba (census tract level)

However, using regression

analysis this research examines:

• whether population density and

other built environment attributes

explain BRT ridership in seven

cities in Latin America

1. Density

2. Diversity

3. Design

4. Destination accessibility

5. Distance to transit

Transit

ridership(# passengers per day)

The five 5 “Ds”

Attributes of the built environment in dimensions

Built environment and travel

6. Parking

7. NMT

infrastructure

8. Socioeconomic

characteristics

9. Facilities and

public spaces

Additional dimensions

TODTransit-oriented

development

Features

Attributes of transit-oriented development (TOD)

• Compact and dense

• High land use mixtures

• High-quality pedestrian environment

• Coordination between transit and the built environment

Transit oriented development TOD

Some benefits of TOD

• Concentrates demand (economies of density)

• Accessibility benefits (local & regional scale)

• Real estate/neighborhood-community development strategy (development around transit stations)

• Generates revenue for the city (ridership, among others)

Built environment and transit ridership

catchment areas around transit stations

measurements of built environment attributes and tests

associations with ridership levels

Heavy Rail

• Taipei

• New York

• Hong Kong

• Seoul

• Montreal

• Nanjing

Light Rail Transit

• Metropolitan Areas

(USA and

Canada)

Gap regarding how

built environment features influence BRT ridership

Bus Rapid Transit

• Bogota

• Los Angeles

Station level studies (aggregated type) on the relationship

between the built environment and transit ridership

1. What is the association between population density and BRT ridership?

Sample of 87 BRT stations in Curitiba

Sample of 120 BRT stations in seven cities in Latin America

2. What are the associations between built environment attributes and BRT ridership?

Sample of 120 BRT stations in seven cities in Latin America

3. Are TOD features associated with BRT ridership?

Built environment factors – TOD features

Cluster analysis – BRT stations typology - clusters

Research questions

Data management Curitiba (N=87)

Detailed area

Sample of 87 BRT stations in Curitiba (excluding

those overlapped with BRT terminals)

• BRT Terminals (n=15) area of study: 0.79 Km2

• BRT stations (n=72) area of study: 0.15 Km2 to

0.20 Km2

BRT stop

overlapped

Overlapped area excluded

from the analysis

Detailed

area

Data collection seven cities (N=120)

Segment

Block

BRT Stop

(buffer area)

BRT Terminal Portal 80Bogota (Colombia)

Segments per BRT stations

(N=120)

108.45 109.75102.38

118.91

136.67

103.90

143.91

0

50

100

150

200

Bogota Sao Paulo Curitiba Goiania CdGuatemala Quito Guayaquil

Sample: 120 BRT stations visited in seven cities

Aggregated data: 13,555 segments and 3,804 blocks studied

N=31 N=12 N=16 N=11 N=9 N=30 N=11

All data aggregated at station level (continuous variables)

Methodology: BRT station level

Segment-level data% of segments in stop

Block-level datadensity or count of instances (0-n)

Station-level data: population density, centrality,

segments density, average distance to BRT stop

BRT Terminal Americas

Bogota (Colombia)BRT Terminal Americas

Bogota (Colombia)

500

700

900

1,100

1,300

1,500

1,700

1,900

2,100

2,300

2,500

0 20 40 60 80 100 120 140 160 180 200

Pre

dic

ted

BR

T r

iders

hip

Population density (people/ha)

Sample BRT Terminals and stations N=87

Sample BRT single stations N=72

Population density is positively associated to BRT ridership

with an elasticity of 0.26

Results CuritibaResearch Question 1

R2 0.8411

R2 0.4260

1,500

2,500

3,500

4,500

5,500

6,500

7,500

8,500

9,500

10,500

11,500

12,500

0 50 100 150 200 250 300 350 400

Pre

dic

ted

BR

T r

ide

rsh

ip

Population density (people/ha)

Population density is not statistically significant (N=120)

Centrality (negatively) and BRT Terminals (positively)

associated with BRT ridership

Results seven cities Latin AmericaResearch question 1

Bogota (+)

Ciudad de Guatemala

Curitiba (+)

GuayaquilQuito

Sao PauloGoiania (+)

Entropy is positively associated with BRT ridership

% segments with high-rise developments and developments (>5

stories) are positively associated with BRT ridership

Results seven cities Latin AmericaResearch question 2

Predicted BRT ridership and entropy(evenness commercial, residential, institutional land uses)

5,000

7,500

10,000

12,500

15,000

17,500

20,000

0 10 20 30 40 50 60 70 80 90 100

Pre

dic

ted

BR

T r

ide

rsh

ip

Percentile

R 2 0.7353

Predicted BRT ridership and developments(% segments high-rise development - % segments with >5 stories)

6,000

7,000

8,000

9,000

10,000

11,000

12,000

13,000

0 10 20 30 40 50 60 70 80 90 100

Pre

dic

ted

BR

T r

ide

rsh

ip

Percentile

High-rise developments >5 stories

R 2 0.7247

R 2 0.7256

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

0 10 20 30 40 50 60 70 80 90 100

Pre

dic

ted

BR

T r

ider

ship

Percentile

NMT friendliness BRT oriented facility index

100,000

125,000

150,000

175,000

200,000

225,000

250,000

0 10 20 30 40 50 60 70 80 90 100

Pre

dic

ted

BR

T r

ider

ship

Percentile

NMT and facilities: positively associated with BRT ridership

BRT Terminals and % segments with high-rise developments:

positively associated with BRT ridership

Predicted BRT ridership, NMT

friendliness and facilities(density of non-motorized transport infrastructure and facilities)

R 2 0.7461

R 2 0.6747

Predicted BRT ridership, Terminals and

high-rise developments(interaction BRT terminals and % segments high-rise developments)

R 2 0.6992

Results seven cities Latin AmericaResearch question 2

8,000

9,000

10,000

11,000

12,000

13,000

14,000

15,000

16,000

17,000

0 10 20 30 40 50 60 70 80 90 100

Pre

dic

ted

BR

T r

ide

rsh

ip

Percentile

High-rise multifamily BRT-oriented mixed land uses Institutional facilities facing BRT corridor

• High-rise multifamily developments, BRT-oriented mixed land uses

• Institutional land uses, facilities, high building heights facing BRT

corridor

Predicted BRT ridership and built environment factors

R 2 0.7184

TOD features with positive association with BRT ridership:

Results seven cities Latin AmericaResearch question 3

C1(0.467)

C2(0.038)

C3(0.335)

C4(ref)

C5(0.024)

C6(0.415)

C7(0.036)

C8(0.003)

C9(0.393)

C10(0.329)

C11(0.326)

C12(0.047)

C13(0.965)

Percentage change 25.99% 144.04% 73.24% 156.79% 110.40% 150.54% 325.63% 31.82% 81.41% 59.06% 161.11% -9.13%

25.99%

144.04%

73.24%

156.79%

110.40%

150.54%

325.63%

31.82%

81.41%

59.06%

161.11%

-9.13%

-50%

0%

50%

100%

150%

200%

250%

300%

350%

Co

eff

icie

nt

aft

er

Ken

ned

y

Predicted percentage change on BRT ridership by cluster (BRT station type)

Results seven cities Latin AmericaResearch question 3

BRT

Terminals

High-rise

multifamily

mixed land

use

Historic

Center

Discussion

• Positive association between population density and BRT

ridership in Curitiba with an elasticity of 0.26

• At the city level, there is a positive association between

population density and BRT ridership in the sample of

BRT stations in Bogota, Curitiba and Goiania

• Population density is not statistically significant in the

data analysis developed with the sample of 120 BRT stations

in seven cities in Latin America

• The introduction of built environment attributes in the

analysis of the sample of 120 BRT stations increases the

explanatory power of the model by 12.3% or 8 percentage

points

Conclusion

• Population density is necessary but not sufficient in order to

achieve high levels of ridership at the BRT station level

• Built environment attributes commonly considered as part

of transit-oriented development (TOD) features are

positively associated with BRT ridership

• Characteristics of urban development typologies around

BRT stations with positive associations with BRT ridership:

• High-rise multifamily and commercial developments

• Mixture of BRT oriented land uses (commercial,

residential and institutional)

• High building heights (more than 5 stories)

• Presence of facilities facing BRT corridors

Applicability in other countries (India)

• Development of BRT Terminals as urban development

projects including:

• High-rise developments

• Mixture of land uses (commercial, residential,

institutional)

• Network of NMT infrastructure

• Implementation of land use planning measures around

current and future BRT stations by promoting:

• Land readjustment schemes

• Public space for NMT infrastructure

• Land developments (> 5 stories)

• Mixture of commercial, residential and institutional land

uses

• Facilities on the BRT right of way.

Policy ImplicationsPromotion of BRT station area plans in two scenarios

• Design and planning stage (future BRT stations):

• Data collection of built environment attributes

• Land use planning regulations

• Land readjustment and value capture measures

• Implementation and operation stage (current BRT stations):

• Base line of TOD features

• Promote high-rise developments around BRT Terminals

• Priority to NMT infrastructure around BRT stations

located in Historic Centers

• Slum upgrading measures in close proximity to BRT

station in low income areas

• Urban renewal and revitalization around BRT stations in

areas with urban decay

Recommendations

Further research on the relationship between the built

environment and transit ridership

• Extend this methodology in other countries implementing

BRT systems (India, Mexico, China, Turkey and South Africa)

• Include additional variables in the analyses such as

socioeconomic data and BRT systems design features

• Test several hypotheses by comparing different buffer

areas addressing methodologically the overlap between BRT

stations

• Data collection for longitudinal studies looking at changes

before and after around BRT stations in order to conduct data

analyses to establish causality on this relationship

Bus Rapid Transit (BRT) and urban development in Latin America and India

Acknowledgements

Professor Daniel A. Rodriguez

Mr. Ramon Munoz-Raskin

Mr. Sam Zimmerman

Dr. Dario Hidalgo

Local Governments

Relatives, colleagues and friends

who supported this research

Amanda Klepper (GIS)