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Webinar Sesion: "Built environment supports for BRT ridership - Evidence from Latin America"

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Webinar Sesion of the BRT Centre of Excellence, presented by Daniel A. Rodriguez & Erik Vergel, on Friday December 18th, 2015

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Webinar Sesion: "Built environment supports for BRT ridership - Evidence from Latin America"

  1. 1. Built environment supports for BRT ridership: Evidence from Latin America Daniel A. Rodríguez, Ph.D. y Erik Vergel, Ph.D. candidate University of North Carolina, Chapel Hill December 18, 2015
  2. 2. Presentation outline  Background  Motivation  Methods  Results  Discussion  Conclusions 2
  3. 3.  Attributes of transit oriented development (TOD):  Compact and dense  High land use mixtures  High-quality pedestrian environment  Strong articulation between transit and environment around it Background: TOD Source: IPPUC (2011) Source: Reconnectingamerica.org`
  4. 4.  Make transit use more viable (TCRP 2008)  Concentrate demand (economies of density)  Balance flows (Stockholm goal)  Real estate/neighborhood development strategy Benefits of TOD
  5. 5.  Generalized perception that the “T” in TOD is rail, not BRT  Lack of locational rigidity & permanence  Noise & pollution  Allure of rails’ newness  All this, despite Curitiba’s exemplary approach Motivation
  6. 6. Built environment & BRT use Heavy Rail • Taipei • New York, SFO • Hong Kong • Seoul • Montreal • Nanjing Light Rail Transit • Metropolitan Areas (USA and Canada) Bus Rapid Transit • Bogota • Los Angeles ? Source: Commuter and Light Rail Transit Corridors: The Land Use Connection
  7. 7.  Given Latin-America’s lead in BRT  (Aim 1) What is occurring around BRT stops?  Examine the built environment around BRT stops  Develop a typology of environments  Help understand where BRT is happening and how  Guide decision makers towards possible future scenarios  (Aim 2) What is the association between the built environment and station-level BRT demand?  Examine individual cities  Understand overall effects Research questions
  8. 8. Presentation outline  Background  Motivation  Methods  Results  Discussion  Conclusions 8
  9. 9.  Collect stop-level data  Inclusion criteria for BRTs  > 5 yrs in operation  Medium to large city  Seven Latin American cities  16% of worlds’ BRT use  31% of Latin America BRT use Methods
  10. 10.  Identify stops with different conditions  Confirmed/reconsidered with local planners Methods City # stops studied % of all # terminals studied % of all Bogotá 26 19.26% 5 55.56% Sao Paulo ABD Corridor 7 9.72% 5 62.50% Curitiba 9 7.32% 7 46.67% Goiânia 6 33.33% 5 71.43% Ciudad de Guatemala 8 57.14% 1 33.33% Quito 24 23.76% 6 54.55% Guayaquil 8 12.31% 3 75.00%
  11. 11.  What to collect? Data collection 1. Density 2. Diversity (use) 3. Design of streets 4. Destination accessibility 5. Distance to transit BRT demand (# pax per day)The five 5 “Ds” 6. Parking 7. NMT infrastructure 8. Socioeconomic characteristics 9. Facilities and public spaces Additional dimensions TOD?
  12. 12.  Environment around each stop  250 m for simple stops (0.2 km2)  500 m for terminal (0.79km2)  Atypical cases (n=8), paired or twin stops Data collection Source: Adjusted by Vergel (2012) from original by Gonzalez & Hartleben (2012) Data source: Google Earth, Gonzalez, Hartleben, Alcaldia de la Ciudad de Guatemala, Fieldwork Data, 2011-2012.
  13. 13.  Modified pedestrian environment data scan Audit tool Tipo de Desarrollo Urbano: Portal _______ Intercambiador________ Parada _________ 0 - 250mts___________250 - 500mts___________ Previo____Durante Const BRT____Posterior BRT_____ 0. Tipo de Segmento 0. Tipo de Segmento 0. Tipo de Segmento 0. Tipo de Segmento 1 1 1 1 2 2 2 2 3 3 3 3 A. Entorno Medio Ambiente Construido A. Entorno Medio Ambiente Construido A. Entorno Medio Ambiente Construido A. Entorno Medio Ambiente Construido 1. Usos del Suelo (seleccionar todos los presentes) 1. Usos del Suelo (seleccionar todos los presentes) 1. Usos del Suelo (seleccionar todos los presentes) 1. Usos del Suelo (seleccionar todos los presentes) 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8 8 8 8 9 9 9 9 10 10 10 10 11 11 11 11 2. Altura Edificios (numero de pisos) 2. Altura Edificios (numero de pisos) 2. Altura Edificios (numero de pisos) 2. Altura Edificios (numero de pisos) 1 1 1 1 1 1 1 1 2_3 2 2_3 2 2_3 2 2_3 2 4_5 3 4_5 3 4_5 3 4_5 3 Mas de 5 Mas de 5 Mas de 5 Mas de 5 No hay ninguno No hay ninguno No hay ninguno No hay ninguno 3. Densidad Urbana 3. Densidad Urbana 3. Densidad Urbana 3. Densidad Urbana Baja 1 Baja 1 Baja 1 Baja 1 Media 2 Media 2 Media 2 Media 2 Alta 3 Alta 3 Alta 3 Alta 3 4. Nivel Consolidacion 4. Nivel Consolidacion 4. Nivel Consolidacion 4. Nivel Consolidacion Bajo 1 Bajo 1 Bajo 1 Bajo 1 Medio 2 Medio 2 Medio 2 Medio 2 Alto 3 3 3 3 5. Estado Construcciones 5. Estado Construcciones 5. Estado Construcciones 5. Estado Construcciones Bajo 1 Bajo 1 Bajo 1 Bajo 1 Medio 2 Medio 2 Medio 2 Medio 2 Alto 3 3 3 3 B. Comentarios Adicionales B. Comentarios Adicionales B. Comentarios Adicionales B. Comentarios Adicionales Frente a Corredor BRT 1 Frente a Corredor BRT 1 Frente a Corredor BRT 1 Frente a Corredor BRT 1 Vehiculos Estacionados en la Calle 2 Vehiculos Estacionados en la Calle 2 Vehiculos Estacionados en la Calle 2 Vehiculos Estacionados en la Calle 2 Desarrollos en Altura 3 Desarrollos en Altura 3 Desarrollos en Altura 3 Desarrollos en Altura 3 Fuera Area de Influencia 4 Fuera Area de Influencia 4 Fuera Area de Influencia 4 Fuera Area de Influencia 4 1 5 1 5 2 6 2 6 3 7 3 7 4 8 4 8 Especificar Otros: Otro 9 Otro 9 Nombre Estacion:__________________ID#:________'_ Fecha:_________________Hora:_______________ Troncal: ________________________________ # Cuadrante:1 ______2______3______4______ BLOCK_ID_N:__________________________ Segmento 1 Segmento 2 Segmento 3 Segmento 4 Via de bajo volumen (2- Carriles) Via de bajo volumen (2- Carriles) Industrial Industrial Industrial Industrial Ciudad: __________________________ID#:________ Tipo de Estacion: Area de Influencia: Via de bajo volumen (2- Carriles) Via de bajo volumen (2- Carriles) Via de alto volumen (3+ Carriles) Via de alto volumen (3+ Carriles) Via de alto volumen (3+ Carriles) Via de alto volumen (3+ Carriles) Segmento Peatonal Segmento Peatonal Segmento Peatonal Segmento Peatonal Comercial/Residencial Comercial/Residencial Comercial/Residencial Comercial/Residencial Comercial NETO Comercial NETO Comercial NETO Comercial NETO Comercial MEDIO Comercial MEDIO Comercial MEDIO Comercial MEDIO Residencial Sencillo Residencial Sencillo Residencial Sencillo Residencial Sencillo Residencial Multifamiliar Residencial Multifamiliar Residencial Multifamiliar Residencial Multifamiliar Industrial/Comercial Industrial/Comercial Industrial/Comercial Industrial/Comercial Alto Alto Alto Parqueaderos Parqueaderos Parqueaderos Parqueaderos Vacante/No desarrollado Vacante/No desarrollado Vacante/No desarrollado Vacante/No desarrollado Institutional Institutional Institutional Institutional Parque/Zona Verde Parque/Zona Verde Parque/Zona Verde Parque/Zona Verde Alto Alto Alto Centro de Salud/Hospital Deportivo/Recreacion Plazoletas Cicloruta Espacio Publico Sistema BRT, Especificar Otros: C. Equipamientos: D. Espacio Publico: Gran Superficie (acceso automovil) Templo/Iglesia Zonas Verdes Alamedas Gran Superficie (acceso peaton) Biblioteca Parques Calles Peatonales Escuela/Centro Educativo Plaza de Mercado/Ferias Plazas Areas Puentes Peatonales
  14. 14.  Secondary data at stop level  Population, roads, distance to central business area Other data sources
  15. 15. Areas audited Stops City Segments Seg/stop Blocks Block/ stop Bogotá 1922 73.9 553 21.3 Sao Paulo ABD 340 48.6 105 15.0 Curitiba 449 49.9 145 16.1 Goiânia 384 64.0 123 20.5 Ciudad de Guatemala 796 100 227 28.4 Quito 1805 75.2 499 20.8 Guayaquil 726 90.8 212 26.5 TOTAL 6,422 1,864
  16. 16. Areas audited Stops Terminals City Segments Seg/stop Blocks Block/ stop Segments Seg/stop Blocks Block/ stop Bogotá 1922 73.9 553 21.3 1440 288.0 395 79.0 Sao Paulo ABD 340 48.6 105 15.0 977 195.4 266 53.2 Curitiba 449 49.9 145 16.1 1189 169.9 312 44.6 Goiânia 384 64.0 123 20.5 924 184.8 267 53.4 Ciudad de Guatemala 796 100 227 28.4 434 434 121 121.0 Quito 1805 75.2 499 20.8 1312 218.7 311 51.8 Guayaquil 726 90.8 212 26.5 857 285.7 274 91.3 TOTAL 6,422 1,864 7,133 1,946
  17. 17.  All data aggregated at stop level, in different ways  Segment-level data  % of segments in stop  Block-level data  density or count of instances (0-n)  Stop-level data  used as continuous variables Data aggregation
  18. 18. Data aggregation
  19. 19.  Factor & cluster analysis Aim 1: Typology X1……...X38 O1 . . . . . . . . O82 Data matrix X1……...X38 O1 . . . . . . . . O82 Data matrix F1...Fk Cluster 1 Cluster 2
  20. 20. Aim 2: Association with population density
  21. 21. Presentation outline  Background  Motivation  Methods  Results  Discussion  Conclusions 21
  22. 22. Aim 1 results: Selected descriptives (N=120) City Mean SD Min Max Facility index 2.75 1.49 0.00 6.00 Facility density 24.55 22.34 0.00 122.23 NMT friendliness 57.03 65.72 0.00 336.13 Residential multifamily 0.15 0.18 0.00 0.87 High density 0.09 0.12 0.00 0.60 High consolidation 0.67 0.26 0.00 1.00 Commercial and parking 0.19 0.16 0.00 0.73 On street parking 0.37 0.19 0.00 0.89 Vacant and BRT 0.02 0.02 0.00 0.16 Population density 74.74 70.31 0.48 390.17
  23. 23.  Cluster 4: Physical barriers  Low scores on commercial variables, density, institutional uses, multi-family units. Barriers  Cluster 5: TOD orientation  High population density with pedestrian infrastructure, green areas, and BRT-oriented public facilities  Cluster 6: Historic Center  Cluster 7: TOD potential, but not there  High density residential multifamily developments, without strong BRT orientation Typology
  24. 24.  Cluster 11: Open space  Undeveloped land, high quality green spaces, with some institutional land uses Typology
  25. 25. Historic center BRT System, Quito Drawing: Vergel, Paredes & Smith, Carolina Transportation Program, DCRP, UNC-Chapel Hill, 2011 Data source: Google Earth, Alcaldia Metropolitana de Quito, Fieldwork Data, 2011-2012 # Built environment factor and popdensity Mean value 1 High-rise multifamily BRT- oriented mixed land use -0.88 2 Vacant unconsolidated urban environment -0.53 3 NMT green areas consolidated 1.75 4 Industrial commercial large blocks off-street parking -0.05 5 Non-core single residential low building heights -1.20 6 BRT-oriented facilities mixed use nearby -0.38 7 Parking -1.53 8 Institutional facilities facing BRT corridor 5.17 9 Non-core affordable housing and informal settlements -0.28 Net population density -0.50
  26. 26. Historic center Fuente: Vergel-Tovar (2011) BRT station Plaza Grande, Quito, Ecuador
  27. 27. TOD potential (n=11) Jardim Botanico BRT System, Curitiba Drawing: Vergel & Paredes, Carolina Transportation Program, DCRP, UNC-Chapel Hill, 2011 Source: Google Earth, IPPUC, URBS Fieldwork Data, 2011-2012. # Built environment factor and popdensity Mean value 1 High-rise multifamily BRT- oriented mixed land use 1.97 2 Vacant unconsolidated urban environment -0.04 3 NMT green areas consolidated -0.51 4 Industrial commercial large blocks off-street parking 0.09 5 Non-core single residential low building heights -1.00 6 BRT-oriented facilities mixed use nearby -0.61 7 Parking 0.06 8 Institutional facilities facing BRT corridor -0.75 9 Non-core affordable housing and informal settlements 0.15 Net population density 0.22
  28. 28. TOD potential (n=11) Source:Vergel-Tovar (2011) BRT station Jardim Botanico, Curitiba, Brazil
  29. 29. Open space stop (n=6) Portal Usme, Bogota BRT System, Bogota Drawing: Vergel & Paredes, Carolina Transportation Program, DCRP, UNC-Chapel Hill, 2011 Source: Google Earth, Secretary of Planning Department of Bogota, Fieldwork Data, 2011-2012 # Built environment factor and popdensity Mean value 1 High-rise multifamily BRT- oriented mixed land use -0.07 2 Vacant unconsolidated urban environment 2.59 3 NMT green areas consolidated 0.13 4 Industrial commercial large blocks off-street parking 0.69 5 Non-core single residential low building heights 0.27 6 BRT-oriented facilities mixed use nearby -0.29 7 Parking -0.45 8 Institutional facilities facing BRT corridor 0.46 9 Non-core affordable housing and informal settlements 1.70 Net population density 0.20
  30. 30. Open space stop (n=6) BRT Terminal Usme, Bogota, Colombia Source:Vergel-Tovar (2011)
  31. 31.  Does the typology capture city-specific factors?  13 clusters  1 Quito Historic Center (Cluster 6, n=1)  1 Ciudad de Guatemala (Cluster 10, n=6)  1 BRT Terminals (Cluster 8, N=21) Discussion
  32. 32.  Surprises  Amount of parking on and off-street  Relatively low density  Little vacant land –regeneration and redevelopment options  Muted role of land uses  Uses are highly mixed, for good and bad  Entropy of 0.64  Compare with 0.25-0.26 for Atlanta; San Francisco Bay Area; Winston-Salem; Chicago Discussion
  33. 33.  Key attributes  Type of residential (multifamily with and without BRT orientation; often without)  High density with pedestrian supports  Institutional uses with green spaces  Presence of low quality housing  Barriers  Industry  Roads Discussion
  34. 34. Physical barriers BRT Station Av Carr. 53A, Bogota, Colombia BRT Station Xaxim, Curitiba, Brazil Source:Vergel-Tovar (2011)
  35. 35. Aim 2 results: Curitiba 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 PredictedBRTridership Population density (people/ha) Sample BRT Terminals and stations N=87 Sample BRT single stations N=72
  36. 36. Aim 2 results: All cities Predicted BRT ridership and entropy 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 PredictedBRTridership Percentile 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 PredictedBRTridership Percentile High-rise developments >5 stories (evenness commercial, residential, institutional land uses)
  37. 37. Aim 2 results: All cities
  38. 38. Prediction BRT ridership and built environment factors Positive associations (Factors 1 and 8) Negative associations (Factor 5) Factor 5 negatively associated with BRT ridership Factors 1 and 8 (TOD features) are positively associated with BRT ridership Integrating aims 1 and 2 Factor 1 High-rise multifamily BRT-oriented mixed land uses Factor 8 Institutional facilities facing BRT corridor R 2 0.7184 R 2 0.7184 Factor 5 Non-core single residential low building heights
  39. 39. Integrating aims 1 and 2 C4 – Typology (reference): industrial areas low density BRT Terminals High-rise multifamily mixed land uses Historic Center High connectivity and density, high-rise developments and mixed land uses Affordable housing, informal settlements, high density Open Space
  40. 40.  Developed a typology of the built environment around BRT stops in Latin America  Highly descriptive  Identifies types that highlight opportunities and barriers  Pedestrian friendliness, parking, redevelopment, access to stops/terminals Conclusions
  41. 41. • Population density necessary but not sufficient for BRT ridership • TOD features positively associated with BRT ridership Conclusions
  42. 42. • 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) • Building heights > 5 stories • Presence of facilities facing BRT corridors Conclusions
  43. 43.  Importance of planning stage  Adapt/modify regulations  Work with land owners/tenants (redevelopment)  Implementation  Promotion of high density development  Promotion of NMT infrastructure  Redevelopment  Public spaces Conclusions
  44. 44.  Funding:  Lincoln Institute for Land Policy, Lee Schipper Memorial Scholarship, Institute for the Study of the Americas  Data collection:  Bogota: Erik Vergel-Tovar, Nicolas Estupinan y Maria Mercedes Maldonado  Sao Paulo: Erik Vergel-Tovar, Marcos Bicahlo, Frederico Roman Ramos, Claudia Acosta, Paula Sakamoto, Daniel Todtmann Montandon, Carlos Joffe, and Magali Jorge  Curitiba: Erik Vergel-Tovar, Debora Ciociola, Irina Cerrutti, Teresa Torres, Adriana Matias, Mauricio Meyer, Oscar Schmeiske, Silvia Mara dos Santos, Anderson Gosmatti, Regina Sorgenfrei  Goainia: Erik Vergel-Tovar, José Carlos Xavier, Domingos Sávio Afonso, Flávia Araújo Xavier, Spyro Angelos Katopodes, Cinthia Machado de Meneses, Julienne Santana de Morais  Guatemala City: Oliver Hartleben, Fabricio Gonzalez, Eddy Morataya.  Quito: Erik Vergel-Tovar, Fernando Puente, Fabricio Castillo, Henry Vilatuna. Sandra Hidalgo, Marcelo Yánez  Guayaquil: Erik Vergel-Tovar, Federico von Buchwald, Felipe Xavier Huerta, Gina Alvarez, Jenny Saade Carriel  GIS and data entry: Julio Paredes, Taylor Smith, S. Kirk, M. Khurana, and Amanda Klepper  All transit agencies in each of the cities studied Acknowledgements

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