To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults

Linchuan Yang, Yibin Ao, Jintao Ke, Yi Lu, Yuan Liang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

Population aging is a conspicuous demographic trend shaping the world profoundly. Walking is a critical travel mode and physical activity for older adults. As such, there is a need to determine the factors influencing the walking behavior of older people in the era of population aging. Streetscape greenery is an easily perceived built-environment attribute and can promote walking behavior, but it has received insufficient attention. More importantly, the non-linear effects of streetscape greenery on the walking behavior of older adults have not been examined. We therefore use readily available Google Street View imagery and a fully convolutional neural network to evaluate human-scale, eye-level streetscape greenery. Using data from the Hong Kong Travel Characteristic Survey, we adopt a machine learning technique, namely random forest modeling, to scrutinize the non-linear effects of streetscape greenery on the walking propensity of older adults. The results show that streetscape greenery has a positive effect on walking propensity within a certain range, but outside the range, the positive association no longer holds. The non-linear associations of other built-environment attributes are also examined.

Original languageEnglish
Article number103099
JournalJournal of Transport Geography
Volume94
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Big data
  • Machine learning
  • Population aging
  • Random forest
  • Streetscape greenery
  • Travel behavior
  • Walking behavior

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Environmental Science(all)

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