Exploration of walking behavior in Vermont using spatial regression.
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Exploration of walking behavior in Vermont using spatial regression.

Filetype[PDF-1.15 MB]


English
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Details:

  • Creators:
    Liu, Lee
  • Corporate Creators:
    University of Vermont. Transportation Research Center
  • Subject/TRT Terms:
  • Publication/ Report Number:
    TRC Report 14-011
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Vermont
  • Corporate Publisher:
    University of Vermont. Transportation Research Center
  • Abstract:
    This report focuses on the relationship between walking and its contributing factors by

    applying spatial regression methods. Using the Vermont data from the New England

    Transportation Survey (NETS), walking variables as well as 170 independent variables are

    derived including some through spatial analysis with Geographic Information Systems

    (GIS). Among those independent variables, people’s lifestyle and perception of the built

    environment variables are included. A linear regression model is first established to serve

    as a base model for comparisons with spatial regression models. The results reveal that

    people’s lifestyle and perception of the built environment are significant variables

    explaining Vermonters’ walking behavior. Methodologically, the results reveal that no

    spatial effect is found and that there are no significant differences between the linear and

    spatial regression models. Therefore, the study concludes that it may be appropriate to

    apply traditional non-spatial statistical tools to analyze the relationship between walking

    and its contributing factors. However, the study suggests that researchers examine

    whether spatial effect exists in these inherently spatial behaviors before using only

    traditional statistics. This caution is particularly relevant as methods to estimate spatial

    models become more commonplace and easily available. The two spatial methods used in

    this report both reveal small but different challenges.

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