Estimating pedestrian and cyclist activity at the neighborhood scale. (July 2016)

• Record Type: Journal Article
• Authors: Salon, Deborah
• Is Part Of: Journal of transport geography. Volume 55(2016)
• Page Start: 11
• Page End: 21
• Publication Date: 2016-07
• Subjects: Walk -- Bicycle -- Neighborhood type -- Road safety -- Small area estimation -- Cluster analysis; Transportation -- Periodicals; Telecommunication -- Periodicals; Transport -- Périodiques; Télécommunications -- Périodiques; Telecommunication; Transportation; Periodicals; 388
• DOI: 10.1016/j.jtrangeo.2016.06.023
• Languages: English
• ISSNs: 0966-6923

Abstract

Abstract: In most parts of the U.S., data on bicycle and pedestrian activity at the neighborhood scale are sparse or non-existent, despite the importance of such data for local planning. Here, a simple small-area estimation method is used to pair travel survey with land use and census data to estimate cyclist and pedestrian activity for census tracts in the state of California. This method is an improvement on fixed per-capita estimates of activity based only on regional or statewide averages. These activity estimates are then used to calculate the intensity of road use by cyclists and pedestrians, and crash rates for these road users. For California, the intensity of pedestrian and cyclist road use in urban census tracts is double that found in suburban tracts, while use in suburban tracts is an order of magnitude greater than that found in rural tracts. Per-capita estimates would suggest substantially smaller differences between neighborhood types. On the safety side, although non-severe crashes involving cyclists and pedestrians are much more likely in more urban areas, severe crash rates for the non-motorized modes exhibit no clear spatial pattern. The method used is simple and easily replicable, potentially filling a critical need for bicycle and pedestrian planners. Highlights: New method developed to estimate cyclist and pedestrian activity for census tracts. Estimates used to calculate cyclist and pedestrian crash rates. Results are an improvement over per-capita activity estimates. Method is simple and replicable, filling a critical need for planners.