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China Planning Network: Urban Transportation Roundtable. June 18, 2009 Beijing. Using Urban Information Systems to Relate Travel Demand to Urban Form Prof. Joseph Ferreira, Jr. Head, Urban Information Systems MIT Urban Studies & Planning Department. Talk Outline.
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China Planning Network: Urban Transportation Roundtable June 18, 2009 Beijing Using Urban Information Systems to Relate Travel Demand to Urban Form Prof. Joseph Ferreira, Jr. Head, Urban Information Systems MIT Urban Studies & Planning Department
Talk Outline • Challenge: managing metro growth • Urbanization & motorization pressure • Unsustainable energy and green-house gas implications • Growth management especially important in China • Opportunity: new tools for ‘responsive’ cities • Measure (in)efficiency of metro growth • Take advantage of new spatial data infrastructure • Example: Metro-Boston growth management • Quantify impact of growth management scenarios • Utilize administrative data • Be sensitive to neighborhood scale • Evaluate benefits of efficient urban form and cost of environmental externalities CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Challenge: Managing Metro Growth • Urbanization & motorization pressure • Rapid motorization: 1000 new cars per day in Beijing • No end in sight • Millions yet to come to cities • Wrong price incentives and weak political will • Unsustainable energy and green-house gas implications • Inefficient urban form and travel patterns due to unpriced externalities • Significant global impact CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Opportunity:New Tools for ‘Responsive’ Cities • Measure (in)efficiency of metro growth • Address unpriced externalities • Make cities ‘responsive’ not rigidly regulated • Take advantage of new spatial data infrastructure • Administrative data now includes location • GIS data layers: roads, buildings, property boundaries… • Transaction info: Transit fare cards, congestion charges, cellphone use… • Build urban models from administrative data • Avoid need for expensive surveys • Enable improved monitoring and discrete choice modeling • Accelerate responsiveness of urban planning • Requires new tools and safeguards • Next-generation urban models (distributed, modular, activity-based) • Locational privacy and anonymized data CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Example: Metro-Boston Growth Management • Illustrate ideas with straightforward example • Class projects work with State and Metro planning agencies • Quantify impact of growth management scenarios • Examine spatial relationships: travel, urban form, and demographics • Extrapolate travel impacts of alternative growth scenarios • Utilize administrative data and official plans • Land use, transportation infrastructure, demographics • Urban activity and travel behavior • Metro growth scenarios and new integrated data layers CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Metro-Boston Regional Planning Key Agencies • State Agencies • EOEEA: Exec. Office of Energy & Environmental Affairs • MassGIS State GIS agency: • ‘Climate Roadmap’ effort: CO2 consequences of urban growth • Registry of Motor Vehicles • Vehicles registration, licensing, and safety inspection records • Metropolitan Area Planning Council (MAPC) • Regional planning agency • part of Boston Metro Planning Organization (MPO) • 101 member Municipalities (out of 164 in metro region) • MetroFuture - ongoing regional planning for 2030 • Central Transportation Planning Staff (CTPS) • Transportation planning part of Boston MPO • Transportation and policy analysis support for Metro Boston • Journey to work and travel time data by traffic analysis zone (TAZ) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Metro Boston United States Massachusetts Boston Metro 164 municipalities (with local land use control) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
MetroFuture Growth Areas, 2000-2030 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Class Project Examples • Collaborate with MAPC and MassGIS • Spring 2008 and 2009 class projects (1/2 semester) • Estimate • VMT (vehicle miles traveled) implications of MAPC growth scenarios • How much extra travel if Boston growth is ‘compact’ vs. ‘sprawl’ • VMT relationship to urban form, neighborhood demographics, and accessibility • Illustrate use of improved GIS and administrative data • Detailed population and business locations • Vehicle miles traveled (VMT) from safety inspections CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Class projects with MAPC and MassGISHalf-semester projects in Advanced GIS class Spring 2008 project: • Estimate non-work travel implications of Alternative MetroFuture Growth Scenarios • PhD and MCP students on project: Wanli Fang, Paul Green, Lissa Harris, Shan Jiang, Masayoshi Oka, Abner Oliveira, Yi Zhu • Project co-supervision with Dr. Fabio Carrera Spring 2009 project: • Examine spatial pattern of VMT across Boston • PhD and MCP students on project: Andrew Gulbrandson, Casey Hunter, Yang Jiang, Jae Seung Lee, Jingsi Xu, Lulu Xue, and Jiyang Zhang • Lab assistance from Mi Diao (advanced PhD student) Most maps shown below are from student work CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
MetroFuture Growth Areas, 2000-2030 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
‘Let It Be’ Scenario ‘Winds of Change’ Scenario Source: MAPC model and MIT 11.521 Project Work (Spring 2008) MetroFuture Forecast for New Housing Demand 2005 - 2030 (by TAZ) +348505 +307476 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
New Grid Layer from MassGIS • Integrate spatially detailed data about • Residences, jobs, businesses • Geography, land use and infrastructure • Private passenger VMT by place of residence • Onto new 250x250 meter grid cell raster • 125K cells for metro Boston • Overlay GIS layers to allocate census population, businesses, employment, and VMT to grid cells CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Mass GIS Allocation of Population to 250x260m Grid Cells …near 2nd ring road, 40 km from Boston CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Business Locations …with Euclidean Distance from Grocery Stores to Grid Cells CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
New VMT Estimates from Safety Inspection Data • Mandatory annual safety inspection • All private passenger autos (5 million in state) • Odometer mileage reported to RMV since 2001 • Estimate annual mileage (VMT) of every vehicle • Geocode every auto to place of residence • Estimate annual mileage from 2+ inspections • Allocate mileage to 250x250m grid cell CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Geocode Vehicles to Residential addressand allocateannual mileage to grid cell • Sources: • MassGIS estimates of annual mileage developed from Registry of Motor Vehicles safety inspection and vehicle registration data • Maps developed by MIT 11.521 class project (Spring 2009) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Spring 2008 Class Project Use new Data to Analyze MetroFuture scenarios • Estimate non-work VMT patterns for current households • Residences from Census and land use data • Destinations from job and business location data • Non-work travel from proximity calculations • Get housing growth locations from MetroFuture scenarios • Let-It-Be (LIB) scenario - business as usual • Wind-of-Change (WOC) scenario - corridor and activity center emphasis • Further details • Assume new growth has VMT behavior of current residents • Account for 16 types of housing + development constraints, etc. CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
‘Let It Be’ Scenario ‘Winds of Change’ Scenario Source: MAPC model and MIT 11.521 Project Work (Spring 2008) New Demand for Housing by 2030 (by TAZ) +348505 +307476 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Source: MIT 11.521 Project Work (Spring 2008) In-Accessibility of non-Work Destinations • Each cell in the grid has a value representative of the total meters traveled one-way for an “average” (non-work)trip for a single household. • Non-Work VMT = Average Non work trip distance (tripmerge) * No of households (hshlds_250m) * 4.18 trips/household CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Source: MIT 11.521 Project Work (Spring 2008) Visualization of Accessibility to Non-Work Destinations Darker colors have higher accessibility (with closer non-work destinations) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Scenario Differences in Estimated VMT CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Lessons from Spring 2008 Class Project • Location of growth can have big impact on non-work travel • Scenario analysis is plausible as two month project • If administrative data, derived GIS layers, and MAPC scenarios are in place • Results are easily explained and accepted CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Spring 2009 Class Project • Next step - look at total travel impact of growth scenarios • Not just non-work travel • Examine actual VMT for every private passenger vehicle in the state for 2005-2008 • 6+ million records from safety inspection data • Visualize and explain VMT variations across metro area CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Geocode Vehicles to Residential addressand allocateannual mileage to grid cell • Sources: • MassGIS estimates of annual mileage developed from Registry of Motor Vehicles safety inspection and vehicle registration data • Maps developed by MIT 11.521 class project (Spring 2009) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Spatial Pattern in Annual Vehicle Miles Traveled (VMT) by 250x250m grid cell …per Vehicle or …per Household Red = low VMT Blue = high VMT Sources: MIT 11.521 project analysis of MassGIS and RMV data CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Annual VMT per Vehicle MIT 11.521 class project work Spring 2009 Annual VMT per Household Annual VMT by Location (250x250m grid cell) CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Demographics Indicators for Metro-Boston Census Block Groups • Thematic maps of: • Household % with kids • Household income • Moved in 45 years (%) • Tenure (% that rent) • etc…. MIT 11.521 class project Spring 2009 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Factor 1: Income and Vehicles Factor 2: Non-standard Families Factor 3: Number of Workers Combine Demographic Indices using Factor Analysis into 3 Primary Factors: MIT 11.521 class project Spring 2009 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Accessibility Indicators Example: Number of jobs accessible in 30 minutes (Shaded TAZ are within 30 minutes by auto from central location near MIT) MIT 11.521 class project Spring 2009 CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Land Use and Urban Form Measures …Use Factor Analysis to build urban form indicators CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009 MIT 11.521 class project Spring 2009
Build VMT Model from Factors VMT [for each 250x250m grid cell] = Function of • Demographic factors • Accessibility factors • Urban Form factors Simple weighted linear regression explains almost 50% of grid cell variation in actual annual mileage. CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Conclusions from Spring 2009 Project • Big differences between city and suburb • Twice the total annual mileage (per household) in the suburbs • Interesting Income effects • Higher income lower VMT per vehicles (but more vehicles) • Higher income much higher VMT per household • Significant demographics, accessibility and urban form effects • Explain 50% of VMT variation across 250x250m grid cells • Non-work accessibility matters • Additional neighborhood variations • Less VMT along transportation corridors & activity centers • Less VMT in mixed use areas • Next step – repeat LIB and WOC comparison • estimate regional benefit of compact development in total VMT CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
General Conclusions • New Tools for ‘Responsive’ Cities • Make cities ‘responsive’ not rigidly regulated • Modern urban information infrastructure can • Accelerate pace of evaluation and response: • Enable self-governance through better measurement of urban form externalities • Scenario analysis is plausible as two month project • If administrative data, derived GIS layers, and MAPC scenarios are in place • Results are easily explained and accepted CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
General Conclusions (Part 2) Take advantage of new spatial data infrastructure • Administrative data now includes location • GIS data layers: roads, buildings, property boundaries… • Transaction info: Transit fare cards, congestion charges, cellphone use… • Build urban models from administrative data • Avoid need for expensive surveys • Enable improved monitoring and discrete choice modeling • Accelerate responsiveness of urban planning • Invest in new tools and safeguards • Next-generation urban models (distributed, modular, activity-based) • Locational privacy and anonymized data CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009
Additional Links • MIT Department of Urban Studies & Planning • Department of Urban Studies & Planning (DUSP): http://dusp.mit.edu • Urban Information Systems (UIS): http://mit.edu/dusp/uis • MassGIS: http://www.mass.gov/mgis • MAPC: http://mapc.org • Related GIS infrastructure sites: • Open Geospatial Consortium (OGC): http://www.opengeospatial.org • Urban and Regional Information Systems Association (URISA): http://www.urisa.org Thank you – Joe Ferreira, jf@mit.edu谢谢! CPN09: Urban Transport Roundtable - Joe Ferreira - June 18, 2009