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HEALTHY COMMUNITY DESIGN
MEASURING INDICATORS OF COMMUNITY HEALTH + HOLISTIC WELL-BEING
BASED ON FUTURE LAND USE + TRANS...
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TABLE OF CONTENTS
HEALTHY COMMUNITY DESIGN FRAMEWORK.......................................................................
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COMMUNITY DESIGN INDICATORS + HEALTH IMPACTS
This section will summarize a cross-sectional scan of planning and public h...
31
This report highlights research conducted during a MITACS Accelerate internship that was completed in the
summer of 201...
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A cross section of project work completed for academic, professional and volunteer projects within the past five years.

Published in: Design
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Active Transportation Consulting Portfolio

  1. 1. 1 HEALTHY COMMUNITY DESIGN MEASURING INDICATORS OF COMMUNITY HEALTH + HOLISTIC WELL-BEING BASED ON FUTURE LAND USE + TRANSPORTATION PLANNING SCENARIOS USING GEOGRAPHIC INFORMATION SYSTEMS Anthony Smith, Ryerson University For: Jennifer Fix, DIALOG Design Vancouver Final Report for 2015 MITACS Accelerate Summer Internship
  2. 2. 2 TABLE OF CONTENTS HEALTHY COMMUNITY DESIGN FRAMEWORK................................................................................................. 3 SCENARIO ANALYSIS PROCESS SUMMARY ........................................................................................... 3 CASE STUDY: CITY OF ABBOTSFORD OFFICIAL COMMUNITY PLAN...................................................... 4 EVERYONE WANTS TO LIVE IN A HEALTHY COMMUNITY................................................................................. 4 HOW CAN WE MEASURE HEALTH + WELL-BEING?............................................................................... 4 WHAT FACTORS INFLUENCE HEALTH + WELL-BEING? ......................................................................... 4 WHAT IS HEALTHY COMMUNITY DESIGN?........................................................................................... 5 WHAT ARE THE BENEFITS OF HEALTHY COMMUNITY DESIGN?........................................................... 5 UNDERSTANDING COMMUNITY CONTEXT + SCALE............................................................................. 6 LOCAL INTERSECTORAL COLLABORATION............................................................................................ 6 COMMUNITY DESIGN INDICATORS + HEALTH IMPACTS .................................................................................. 7 DESIGN INDICATOR TYPOLOGIES.......................................................................................................... 7 DESIGN INDICATOR LITERATURE REVIEW............................................................................................. 8 DISCUSSION: CITIES FOR PEOPLE.................................................................................................................... 12 APPENDIX A: ABBOTSFORD OFFICIAL COMMUNITY PLAN PROJECT DETAILS ................................................ 15 DEVELOPMENT OF POPULATION SCENARIOS .................................................................................... 15 BUILDING TYPOLOGIES ....................................................................................................................... 17 FUTURE EMPLOYMENT SCENARIODEVELOPMENT................................................................................ 19 FUTURE TRANSPORTATION NETWORK............................................................................................... 21 PUBLIC ENGAGEMENT MAPS AND DESIGN INDICATOR DASHBOARD ............................................... 22 APPENDIX B: GIS INDICATOR CALCULATION METHODS................................................................................ 24 ROAD NETWORK INTERSECTION DENSITY.......................................................................................... 24 NATURAL AREAS.................................................................................................................................. 24 GROCERY STORES................................................................................................................................ 24 APPENDIX C: GHG EMISSION CALCULATIONS................................................................................................. 26 APPENDIX D: MITACS PROJECT OVERVIEW .................................................................................................... 28 DESCRIPTION OF PRIMARY INTERNSHIP ACTIVITIES........................................................................... 28 ADDITIONAL INTERNSHIP ACTIVITIES ................................................................................................. 29 PROJECT RESEARCH BACKGROUND.................................................................................................... 29
  3. 3. 7 COMMUNITY DESIGN INDICATORS + HEALTH IMPACTS This section will summarize a cross-sectional scan of planning and public health research that relied on objective measures of community design calculated using GIS. This discussion has been grouped into 11 planning and design categories related to each of the community design indicators identified in the conceptual community design indicator framework. DESIGN INDICATOR TYPOLOGIES To focus the scope of this review, it is important to contextualize the characteristics of the CDIs that will be considered in this study, to be clear about what they are – and are not. Broadly speaking, the type of CDIs used in this study could also be described as healthy built environment indicators or planning performance indicators. Additionally, CDIs can be calculated based on many different methods, geographic scales, and time periods. This review will consider evidence from studies that are based on individual household or postal code locations, neighbourhoods, or city regions. In some cases, individual indicators have often been calculated based on circular buffers or network-based walksheds surrounding a home location or postal code. This approach provides a ‘custom’ neighbourhood for each resident that may improve the accuracy of measurement and better reflect individual exposure to local residential environments. For example, Oliver, Schuurman, & Hall (2007) compared circular and network buffers to examine the influence of land use on walking for leisure and errands and found a significant relationship between walking and built environment based on land use mix within 800-metre network-based buffers. Alternatively, CDIs can be constructed based on larger scale sample areas, such as urban centres or municipalities. For example, the performance indicators used to assess the Growth Plan for the Greater Golden Horseshoe in Ontario were calculated based on municipalities and within specific sub-city-scale planning areas such as urban centres or transit-oriented development zones (Government of Ontario, 2015). The current study will include CDIs that are based on the following five spatial analysis methods. 1. Area Indicators based on the fraction of a study area polygon that is covered by a certain feature. 2. Density Indicators based on the number of points, the length of lines, number of polygons, or summaries of other spatial attributes such as population totals within a given study area. These measures must always be standardized and expressed per unit area. Reporting raw feature counts can result in bias due to study area size variability. 3. Population or Access Indicators are based on the proportion of the population within a study area that lives within a specified distance from a point, line or polygon feature. These are expressed as a fraction of the total population with access, divided by the total population of a study area. Moreover, these measures can be based on spatial buffers such as circles from points, or network-based buffers that are often called ‘walksheds’ or ‘drivesheds’. 4. Distance Indicators examine the location of a study area relative to one or more external locations. 5. Index or Ratio Indicators are derived from primary measures. These indicators can take many forms. Each of these indicator typologies can be calculated based on existing spatial data for a community, or based on modelled or constructed scenarios related to future growth scenarios. Results can then be directly compared across time or between scenarios to evaluate direct impacts of planning and design decisions. Based on the evidence presented in the following section, these impacts can then be related to potential health and well-being outcomes.
  4. 4. 31 This report highlights research conducted during a MITACS Accelerate internship that was completed in the summer of 2015.This report was produced by Anthony Smith, a Graduate Student in the Master of Urban Planning Program in the School of Urban and Regional Planning at Ryerson University. This project was inspired and supervised by Jennifer Fix, an Associate planner and urban designer at DIALOG Design Vancouver. Academic supervision was provided by Dr. Raktim Mitra, a faculty member in the School of Urban and Regional Planning at Ryerson. Anthony would also like to thank Martin Neilson, Esteban Matheus, Molly Steeves and many other DIALOG team members and City of Abbotsford staff who provided valuable input to this project.

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