Pedestrian volume information is critical to study traffic safety as well as to plan for pedestrian friendly design. We present a model used to estimate the pedestrian volumes for street intersections in the city of San Francisco, California. Through regression analysis at multiple geographical scales, a set of socioeconomic variables and built-environment characteristics were examined. Three factors emerged as having strong explanatory power on the variances of pedestrian volume: population and job density, local transit access, and land use mix. It was found that the strongest area of influence on pedestrian traffic is around a one-block radius of an intersection. Multiple-scale analysis reveals that not all variables are significant at the same scale. In fact, the best model was obtained when a mix of scales was used. Because the analysis in this paper utilizes easy-to-access data and routine statistical analysis, it is easy to apply it in other cities, hence providing a valuable tool for geographers, public health professionals, urban planners, and transportation engineers.


Additional Information

Print ISSN
pp. 164-181
Launched on MUSE
Open Access
Back To Top

This website uses cookies to ensure you get the best experience on our website. Without cookies your experience may not be seamless.