Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia

Jiacheng Jiao, John Rollo, Baibai Fu and Chunlu Liu
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Jiacheng Jiao: School of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, Australia
John Rollo: School of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, Australia
Baibai Fu: Key Laboratory of Digital Simulation in Architecture and Urban-Rural Spatial Design, Universities of Shandong, Jinan 250101, China
Chunlu Liu: School of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, Australia

Land, 2021, vol. 10, issue 6, 1-17

Abstract: Previous studies have mostly examined how sustainable cities try to promote non-motorized travel by creating a walking-friendly environment. Such existing studies provide little data that identifies how the built environment affects pedestrian volume in high-density areas. This paper presents a methodology that combines person correlation analysis, stepwise regression, and principal component analysis for exploring the internal correlation and potential impact of built environment variables. To study this relationship, cross-sectional data in the Melbourne central business district were selected. Pearson’s correlation coefficient confirmed that visible green ratio and intersection density were not correlated to pedestrian volume. The results from stepwise regression showed that land-use mix degree, public transit stop density, and employment density could be associated with pedestrian volume. Moreover, two principal components were extracted by factor analysis. The result of the first component yielded an internal correlation where land-use and amenities components were positively associated with the pedestrian volume. Component 2 presents parking facilities density, which negatively relates to the pedestrian volume. Based on the results, existing street problems and policy recommendations were put forward to suggest diversifying community service within walking distance, improving the service level of the public transit system, and restricting on-street parking in Melbourne.

Keywords: built environment; pedestrian volume; stepwise regression; principal component analysis; Melbourne (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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