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Estimating pedestrian and cyclist activity at the neighborhood scale

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  • Salon, Deborah

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.

Suggested Citation

  • Salon, Deborah, 2016. "Estimating pedestrian and cyclist activity at the neighborhood scale," Journal of Transport Geography, Elsevier, vol. 55(C), pages 11-21.
    • Handle: RePEc:eee:jotrge:v:55:y:2016:i:c:p:11-21
    DOI: 10.1016/j.jtrangeo.2016.06.023
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    References listed on IDEAS

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    1. Griswold, Julia B. & Medury, Aditya & Schneider, Robert J., 2011. "Pilot Models for Estimating Bicycle Intersection Volumes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt380855q6, Institute of Transportation Studies, UC Berkeley.
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    2. Iacopo Bernetti & Veronica Alampi Sottini & Lorenzo Bambi & Elena Barbierato & Tommaso Borghini & Irene Capecchi & Claudio Saragosa, 2020. "Urban Niche Assessment: An Approach Integrating Social Media Analysis, Spatial Urban Indicators and Geo-Statistical Techniques," Sustainability, MDPI, vol. 12(10), pages 1-26, May.
    3. Guimpert, Ignacio & Hurtubia, Ricardo, 2018. "Measuring, understanding and modelling the Walking Neighborhood as a function of built environment and socioeconomic variables," Journal of Transport Geography, Elsevier, vol. 71(C), pages 32-44.
    4. Robert J. Schneider & Lingqian Hu & Joseph Stefanich, 2019. "Development of a neighborhood commute mode share model using nationally-available data," Transportation, Springer, vol. 46(3), pages 909-929, June.

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