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Theme 7 Broader interactions, public transportation and city form

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  • 1. © P. Christopher Zegras 9/24/2013 1 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 2 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
  • 3. © P. Christopher Zegras 9/24/2013 3 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
  • 4. © P. Christopher Zegras 9/24/2013 4 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
  • 5. © P. Christopher Zegras 9/24/2013 5 Paris Angel et al, 2011 9 Bandung, Indonesia Angel et al, 2011 10
  • 6. © P. Christopher Zegras 9/24/2013 6 Average Tract Density: 20 US Metro Areas Angel et al., 2011 11 World “Suburbanization” Trends Angel et al., 2011 12
  • 7. © P. Christopher Zegras 9/24/2013 7 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.
  • 8. © P. Christopher Zegras 9/24/2013 8 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
  • 9. © P. Christopher Zegras 9/24/2013 9 Macro- Scale Form & Function Bertaud, 2004 17 18 Micro Scale Built Environment Crane, 1996
  • 10. © P. Christopher Zegras 9/24/2013 10 19 Formalizing the Theoretical Framework 20 Crane’s Trip-Based (Time/Cost-Based) Framework Crane, 1996
  • 11. © P. Christopher Zegras 9/24/2013 11 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
  • 12. © P. Christopher Zegras 9/24/2013 12 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
  • 13. © P. Christopher Zegras 9/24/2013 13 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).
  • 14. © P. Christopher Zegras 9/24/2013 14 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
  • 15. © P. Christopher Zegras 9/24/2013 15 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
  • 16. © P. Christopher Zegras 9/24/2013 16 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
  • 17. © P. Christopher Zegras 9/24/2013 17 “Micro-Scale” Effects Meta-Analysis, Case Study (Jinan) 33 Meta-Analysis: Elasticities of Walking with respect to BE Ewing and Cervero, 2010. 34
  • 18. © P. Christopher Zegras 9/24/2013 18 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
  • 19. © P. Christopher Zegras 9/24/2013 19 Arterial- Edge Corridor (Jingshi St.) 1 (Jiang 2010) 37 Integrated- Boulevard Corridor (Lishan Rd.) 2 (Jiang 2010) 38
  • 20. © P. Christopher Zegras 9/24/2013 20 Below- Expressway Corridor (Beiyuan St.) 3 (Jiang 2010) 39 Approach , , , ;   • Station area user survey • Built Environment Analysis • Regression 40
  • 21. © P. Christopher Zegras 9/24/2013 21 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
  • 22. © P. Christopher Zegras 9/24/2013 22 Distance… (Jiang 2010) 43 (Jiang 2010) 44
  • 23. © P. Christopher Zegras 9/24/2013 23 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
  • 24. © P. Christopher Zegras 9/24/2013 24 Walk next to trees… Arterial-Edge Corridor 47 (Jiang 2010) Walk under trees… Integrated-Boulevard Corridor 48 (Jiang 2010)
  • 25. © P. Christopher Zegras 9/24/2013 25 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
  • 26. © P. Christopher Zegras 9/24/2013 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
  • 27. © P. Christopher Zegras 9/24/2013 27 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
  • 28. © P. Christopher Zegras 9/24/2013 28 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
  • 29. © P. Christopher Zegras 9/24/2013 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
  • 30. © P. Christopher Zegras 9/24/2013 30 Make crossing safer… (Jiang 2010) 59 Put more trees and stores along the sidewalk in an appropriate way… (Jiang 2010) 60
  • 31. © P. Christopher Zegras 9/24/2013 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
  • 32. © P. Christopher Zegras 9/24/2013 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
  • 33. © P. Christopher Zegras 9/24/2013 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
  • 34. © P. Christopher Zegras 9/24/2013 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
  • 35. © P. Christopher Zegras 9/24/2013 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
  • 36. © P. Christopher Zegras 9/24/2013 36 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
  • 37. © P. Christopher Zegras 9/24/2013 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
  • 38. © P. Christopher Zegras 9/24/2013 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
  • 39. © P. Christopher Zegras 9/24/2013 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
  • 40. © P. Christopher Zegras 9/24/2013 40 Hidalgo, 2006. Calle 13 – Av. Caracas 79 Vehicles Graftieaux, 2005. 80
  • 41. © P. Christopher Zegras 9/24/2013 41 Stations Graftieaux, 2005. 81 1.5 km buffer 82
  • 42. © P. Christopher Zegras 9/24/2013 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
  • 43. © P. Christopher Zegras 9/24/2013 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
  • 44. © P. Christopher Zegras 9/24/2013 44 Commercial Development Hidalgo, 2006. 87 Commercial Development Hidalgo, 2006. 88
  • 45. © P. Christopher Zegras 9/24/2013 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
  • 46. © P. Christopher Zegras 9/24/2013 46 Canoga Orange Line Station (LA) 91 Canoga Orange Line Station 92
  • 47. © P. Christopher Zegras 9/24/2013 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
  • 48. © P. Christopher Zegras 9/24/2013 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
  • 50. © P. Christopher Zegras 9/24/2013 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
  • 51. © P. Christopher Zegras 9/24/2013 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
  • 52. © P. Christopher Zegras 9/24/2013 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
  • 53. © P. Christopher Zegras 9/24/2013 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
  • 54. © P. Christopher Zegras 9/24/2013 54 Residential Densities Along Structural Axes and Adjoining Neighborhoods TCRP, 2003. 107 Appendix 3 Transmilenio apartment rent price effects 108
  • 55. © P. Christopher Zegras 9/24/2013 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
  • 56. © P. Christopher Zegras 9/24/2013 56 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
  • 57. © P. Christopher Zegras 9/24/2013 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
  • 58. © P. Christopher Zegras 9/24/2013 58 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
  • 59. © P. Christopher Zegras 9/24/2013 59 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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