Openly accessible

Exploring effective built environment factors for evaluating pedestrian volume in high-density areas: a new finding for the Central Business District in Melbourne, Australia

Jiao, Jiacheng, Rollo, John, Fu, Baibai and Liu, Chunlu 2021, Exploring effective built environment factors for evaluating pedestrian volume in high-density areas: a new finding for the Central Business District in Melbourne, Australia, Land, vol. 10, no. 6, pp. 1-17, doi: 10.3390/land10060655.

Attached Files
Name Description MIMEType Size Downloads

Title Exploring effective built environment factors for evaluating pedestrian volume in high-density areas: a new finding for the Central Business District in Melbourne, Australia
Author(s) Jiao, JiachengORCID iD for Jiao, Jiacheng orcid.org/0000-0003-3888-1977
Rollo, JohnORCID iD for Rollo, John orcid.org/0000-0003-3888-1977
Fu, Baibai
Liu, ChunluORCID iD for Liu, Chunlu orcid.org/0000-0003-1144-4355
Journal name Land
Volume number 10
Issue number 6
Article ID 655
Start page 1
End page 17
Total pages 17
Publisher MDPI AG
Place of publication Basel, Switzerland
Publication date 2021
ISSN 2073-445X
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Environmental Studies
Environmental Sciences & Ecology
built environment
pedestrian volume
stepwise regression
principal component analysis
Melbourne
GOOGLE STREET VIEW
LAND-USE
ADULTS WALKING
INDEXES
TRAVEL
SPACE
ACCESSIBILITY
DETERMINANT
HABITAT
Summary 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.
Language eng
DOI 10.3390/land10060655
Indigenous content off
Field of Research 0502 Environmental Science and Management
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30152833

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 30 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Thu, 24 Jun 2021, 16:11:28 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.