Creating a Walkability Data Set and Prediction Map Using the
Walk ScoreTM Algorithm
John Whalen, M.A.Department of Geography
The State University of New York at Buffalo
February 25th, 2012
Definition of Walkability
- How conducive is the built environment to personal vehicle independence for everyday activities?
- Influenced by numerous aspects, such as density, land use, street connectivity, etc.
- Many proposed methods to quantify
Walkability Has Been Linked To
- Increased physical activity- Lower likelihood of obesity- Less fossil-fuel consumption from cars- Less air pollution from cars- Increased property values
Walk Score
www.walkscore.comGives any location a score from 0-100 based on
the variety and proximity of nearby commercial facilities
Looks for closest facilities in five categories: education, retail, food, recreation, and entertainment.
Transit Score
- 0-100 score rating public transportation access- Based on proximity to transit stops, type of
transportation and frequency of stops.- Available in about 150 cities
Walk Score - Pros
- Free to use- International scale (US, Canada, UK, Ireland,
Australia, New Zealand)- Uses a dynamic data set- Eliminates the necessity to gather data sets
from many different agencies
Walk Score - Limitations
- Straight-line (as the crow flies) distances- Natural barriers/hindrances are disregarded
(i.e. bodies of water, slope, weather, etc)- Assumes existence of pedestrian paths- Public Transit not considered- Source data concerns
Validation for Research PurposesCarr LJ, Dunsiger SI, Marcus BH. (2010). Walk score™ as a global estimate of
neighborhoodwalkability. American Journal of Preventive Medicine. 39(5):460-3.
Carr LJ, Dunsiger SI, Marcus BH. (2011) Validation of Walk Score for estimating access to
walkable amenities. British Journal of Sports Medicine. 45(14):1144-8.
Duncan DT, Aldstadt J, Whalen J, Melly SJ, and Gortmaker SL. (2011). Validation of Walk
Score® for Estimating Neighborhood Walkability: An Analysis of Four US Metropolitan
Areas. International Journal of Environmental Research and Public Health. 8(11): 4160-
4179.
Duncan DT, Aldstadt J, Whalen J, and Melly SJ. (in press). Validation of Walk Scores and
Transit Scores for Estimating Neighborhood Walkability and Transit Availability: A Small-
Area Analysis. GeoJournal. DOI: 10.1007/s10708-011-9444-4
Walk Score API
- Application Programming Interface (API)- Interface created in R to query Walk Score API
with lat/long coordinates, returns Walk and Transit Scores
- Greatly accelerates mass-data collection- Available from CRAN – “walkscoreAPI”
Walk Score Prediction Map
Heat map to see spatial patterns Walk Score and Transit Score on city-wide scale.
Sample area – Buffalo, NY
Sampling
Lat/Long coordinates of each Census Block centroid found
Used as input parameters for API calls
Uploaded to ArcMap as points
InterpolationOrdinary kriging – no trend removal, Gaussian
model6 Neighbors, at least 3 included
Buffalo NY
Walk Score prediction map
Buffalo NY
Transit Score prediction map
Buffalo NY
Walk Score +Transit Score
Works CitedLo, R. H. (2009). "Walkability: What is it?" Journal of Urbanism:
International Research on Placemaking and Urban Sustainability 2(2): 145-166.
Frank, L. D. and P. Engelke (2005). "Multiple Impacts of the Built Environment on Public Health: Walkable Places and the Exposure to Air Pollution." International Regional Science Review 28(2): 193-216.
Owen, N., E. Leslie, et al. (2000). "Environmental Determinants of Physical Activity and Sedentary Behavior." Excercise & Sport Sciences Reviews 28(4): 153-158.
Frank, L. D. and P. Engelke (2005). "Multiple Impacts of the Built Environment on Public Health: Walkable Places and the Exposure to Air Pollution." International Regional Science Review 28(2): 193-216.
Pivo, G. and J. Fisher (2009). "Effects of Walkability on Property Values and Investment Returns." Working Paper.
Front Seat (2010). Walk Score Methodology. Seattle, WA, Front Seat.R Development Core Team (2010). R: A Language and Environment for
Statistical Computing., R Foundation for Statistical Computing, Vienna, Austria.
Cressie, N. (1990). "The origins of kriging." Mathematical Geology 22(3): 239-252.
Whalen, J. (2011). "WalkscoreAPI Walk Score and Transit Score API." R Package version 1.0.