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Step 1. Data Collection: Data from SF OpenData, ESRI Business Analysis Data, Transportation Injury Mapping System (TIMS), USGS, Urban Forest Map, NASA Socioeconomic Data and Applications Center, EPA Envirofacts, and CA State Water Resources Control Board GeoTracker was organized and cleaned Step 2. Geocode Addresses: Created a point shapefile of toxic sites Step 3. Service Area Analysis: Constructed a 0.25 mi service area containing restaurants/cafes, grocery stores, schools, and shops Step 4. Create Buffers: Walk Score (250 ft buffer for sidewalks, 100 ft for pedestrian collisions, 500 ft for serious crime); Environment Score (25 ft buffer for trees, 0.25 mi for parks and toxic sites, 2 mi for superfund sites, and 500 ft for poor air quality sites and industrial land) Step 5. Conduct Slope Analysis: Using a slope-to-polygon conversion, steep slopes were isolated and added to the map as one layer (where the slope is greater than 5%, which reflects ADA standards for ramps) Step 6. Determine Formulas: Added weights to Attribute Tables for both Opportunities and Constraints Step 7. Create Opportunity & Constraint Maps: Joined Walk and Environment opportunity layers to create composite opportunity map. Joined Walk and Environment constraint layers to create composite constraint map Step 8. Create Walk & Environment Score Maps: Joined opportunity and constraint layers to create composite Walk Score and Environment Score maps Step 9. Analyze Findings: Analyzed map results to answer our research question ARE SAN FRANCISCO’S MOST WALKABLE SITES HEALTHY PLACES TO LIVE? Paige Roosa, Sarah Saviskas, and Yiyang Yu • CP 204c • Final Project • May 2016 PROBLEM: Walk Score, Transit Score, and Bike Score models are widely used when considering neighborhood quality, but they fail to take into account environmental factors, which may enhance or degrade a neighborhood’s livability. A neighborhood might be very walkable, transit-friendly, and bikeable, but have qualities that are detrimental to residents’ health. We created an Environment Score and compared that to a Walk Score that we constructed for the City of San Francisco. CONCLUSIONS & IMPLICATIONS IDEAS FOR IMPROVEMENT FINDINGS ASSUMPTIONS • Consider additional opportunity and constraint factors in the analysis • Collect a more comprehensive dataset (e.g. trees missing in parks; retail could be more filtered) • Use a more informed weighting strategy; Consult the public and experts • Add a second tier service area for amenities within 0.5 miles • Complete Suitability Analysis Walk Score Opportunities Walk Score Constraints Environment Score Constraints • Restaurants/Cafes • Grocery stores • Schools • Shops • Sidewalk availability +2 +3 +3 +2 +3 • Serious crime - 2014 burglaries, robberies, assaults • Steep slopes • Pedestrian collisions -3 -3 -2 Environment Score Opportunities • Tree coverage • Parks +2 +2 • Superfund sites • Air quality - active, industrial point sources of pollution • Toxic sites • Industrial land -4 -4 -3 -2 Total Opportunity Projection: NAD83 (2011) State Plane California III FIPS 0403 Feet Total Constraint Walk Score Environment Score • Walkable areas in San Francisco are not necessarily the healthiest places to live • Walkability and environmental constraints are not distributed evenly – Southwest SF has the fewest opportunities & constraints, whereas Downtown/ Financial District has the most • Developments applying for Low Income Housing Tax Credits that are located in walkable areas may be near more environmental hazards • Our results may be an impetus for prioritizing clean-up of environmentally-burdened sites in walkable areas • An official Environment Score should be developed! South Beach SoMa Central Waterfront/ Dogpatch Bayview Areas of Concern * *Areas with high walk scores and many environmental hazards 0 1 2 0.5 Miles
