Estimation of urban transport accessibility at the spatial resolution of an individual traveler

Itzhak Benenson, Eran Ben-Elia, Yodan Rofe, Amit Rosental

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Accessibility, particularly for public transport users is an important consideration in sustainable mobility policies. Various accessibility measures have been suggested in the literature, most at coarse aggregate spatial resolution of zones or neighborhoods. Based on recently available Big Urban GIS data our aim is to measure accessibility from the viewpoint of an individual traveler who traverses the transportation network from one building as origin to another at the destination. We estimate transport accessibility by car and by public transport based on mode-specific travel times and corresponding paths, including walking and waiting. A computational application that is based on the intensive querying of relational database management systems is developed to construct high-resolution accessibility maps for an entire metropolitan area. It is tested and implemented in a case study involving the evaluation of a new light rail line in the metropolitan area of Tel Aviv. The results show essential dependence of accessibility estimates on spatial resolution—high-resolution representations of the trip enable unbiased estimates. Specifically, we demonstrate that the contribution of the LRT to accessibility is overrated at low resolutions and for longer journeys. The new approach and fast computational method can be employed for investigating the distributional effects of transportation infrastructure investments and, further, for interactive planning of the urban transport network.

Original languageEnglish
Title of host publicationSpringer Geography
PublisherSpringer
Pages383-404
Number of pages22
DOIs
StatePublished - 2017

Publication series

NameSpringer Geography
ISSN (Print)2194-315X
ISSN (Electronic)2194-3168

Keywords

  • Accessibility
  • Big data
  • GIS
  • Graph database
  • High-resolution spatial analysis
  • Public transport

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