Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia
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 meth...
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| Format: | Article |
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MDPI AG
2021-06-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/10/6/655 |
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| author | Jiacheng Jiao John Rollo Baibai Fu Chunlu Liu |
| author_facet | Jiacheng Jiao John Rollo Baibai Fu Chunlu Liu |
| author_sort | Jiacheng Jiao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T10:16:02Z |
| format | Article |
| id | doaj.art-e0a431785efc4a85b014469bbde9f866 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-10T10:16:02Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-e0a431785efc4a85b014469bbde9f8662023-11-22T00:53:14ZengMDPI AGLand2073-445X2021-06-0110665510.3390/land10060655Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, AustraliaJiacheng Jiao0John Rollo1Baibai Fu2Chunlu Liu3School of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, AustraliaSchool of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, AustraliaKey Laboratory of Digital Simulation in Architecture and Urban-Rural Spatial Design, Universities of Shandong, Jinan 250101, ChinaSchool of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, AustraliaPrevious 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.https://www.mdpi.com/2073-445X/10/6/655built environmentpedestrian volumestepwise regressionprincipal component analysisMelbourne |
| spellingShingle | Jiacheng Jiao John Rollo Baibai Fu Chunlu Liu 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 built environment pedestrian volume stepwise regression principal component analysis Melbourne |
| 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 |
| title_full | Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia |
| title_fullStr | Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia |
| title_full_unstemmed | Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia |
| title_short | Exploring Effective Built Environment Factors for Evaluating Pedestrian Volume in High-Density Areas: A New Finding for the Central Business District in Melbourne, Australia |
| title_sort | exploring effective built environment factors for evaluating pedestrian volume in high density areas a new finding for the central business district in melbourne australia |
| topic | built environment pedestrian volume stepwise regression principal component analysis Melbourne |
| url | https://www.mdpi.com/2073-445X/10/6/655 |
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