Exploring the non-linear associations between spatial attributes and walking distance to transit

Tao Tao, Jueyu Wang, Xinyu Cao

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

When examining environmental correlates of walking distance to transit stops, few studies report the importance of spatial attributes relative to other factors. Furthermore, previous studies often assume that they have linear relationships with walking distance. Using the 2016 Transit On Board Survey in the Minneapolis and St. Paul Metropolitan Area, this study adopted the gradient boosting decision trees method to examine the relationships between walking distance and spatial attributes. Results showed that spatial attributes collectively have larger predictive power than other factors. Moreover, they tend to have non-linear associations with walking distance. We further identified the most effective ranges of spatial attributes to guide stop area planning and stop location choice in the region.

Original languageEnglish (US)
Article number102560
JournalJournal of Transport Geography
Volume82
DOIs
StatePublished - Jan 2020

Keywords

  • Built environment
  • Land use
  • Machine learning
  • Station area planning
  • Walking behavior

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