Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne
Urban green spaces (UGSs) provide city residents contact with nature, offering mental and physical health benefits. However, residents’ access to green spaces in cities can be associated with their socioeconomic status (SESs). This study utilizes the Kernel Density tool as an innovative method to me...
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MDPI AG
2025-04-01
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| author | Parian Hoseini Pooriya Mohseni Piret Veeroja Greg Foliente |
| author_facet | Parian Hoseini Pooriya Mohseni Piret Veeroja Greg Foliente |
| author_sort | Parian Hoseini |
| collection | DOAJ |
| description | Urban green spaces (UGSs) provide city residents contact with nature, offering mental and physical health benefits. However, residents’ access to green spaces in cities can be associated with their socioeconomic status (SESs). This study utilizes the Kernel Density tool as an innovative method to measure UGS inequities and their relationship with cardiovascular disease (CVD) rates. Next, the UGS patterns and their potential implications for CVD are examined across suburbs with a range of SES levels in Melbourne, Australia. The proposed method is tested in conjunction with two commonly used measures of accessibility (Network Analysis) and provision (UGS per capita). The results show that more advantaged suburbs have better access to UGS and lower CVD rates. Moreover, the analysis reveals that a more geographically dispersed UGS pattern, predominantly observed in higher SES suburbs, can be associated with lower CVD than a concentrated pattern, and the integration of the SES and UGS indicators through Kernel Density analysis reveals that inequitable access to green spaces disproportionately impacts the health incomes of socioeconomically disadvantaged communities. Finally, the Kernel Density and Network Analysis tools in ArcGIS can serve as effective supplementary methods for addressing similar considerations in UGS planning and policy. |
| format | Article |
| id | doaj-art-83bccb6eafa749fa8f41d3d97cd3ff0d |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-83bccb6eafa749fa8f41d3d97cd3ff0d2025-08-20T03:08:44ZengMDPI AGApplied Sciences2076-34172025-04-01157394010.3390/app15073940Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan MelbourneParian Hoseini0Pooriya Mohseni1Piret Veeroja2Greg Foliente3School of Built Environment, University of New South Wales, Kensington 2033, AustraliaSchool of Civil & Environmental Engineering, University of New South Wales, Kensington 2033, AustraliaCentre for Urban Transition, Swinburne University of Technology, Hawthorn 3122, AustraliaDepartment of Infrastructure Engineering, The University of Melbourne, Parkville 3010, AustraliaUrban green spaces (UGSs) provide city residents contact with nature, offering mental and physical health benefits. However, residents’ access to green spaces in cities can be associated with their socioeconomic status (SESs). This study utilizes the Kernel Density tool as an innovative method to measure UGS inequities and their relationship with cardiovascular disease (CVD) rates. Next, the UGS patterns and their potential implications for CVD are examined across suburbs with a range of SES levels in Melbourne, Australia. The proposed method is tested in conjunction with two commonly used measures of accessibility (Network Analysis) and provision (UGS per capita). The results show that more advantaged suburbs have better access to UGS and lower CVD rates. Moreover, the analysis reveals that a more geographically dispersed UGS pattern, predominantly observed in higher SES suburbs, can be associated with lower CVD than a concentrated pattern, and the integration of the SES and UGS indicators through Kernel Density analysis reveals that inequitable access to green spaces disproportionately impacts the health incomes of socioeconomically disadvantaged communities. Finally, the Kernel Density and Network Analysis tools in ArcGIS can serve as effective supplementary methods for addressing similar considerations in UGS planning and policy.https://www.mdpi.com/2076-3417/15/7/3940environmental justicephysical healthurban green space planningurban development policy |
| spellingShingle | Parian Hoseini Pooriya Mohseni Piret Veeroja Greg Foliente Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne Applied Sciences environmental justice physical health urban green space planning urban development policy |
| title | Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne |
| title_full | Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne |
| title_fullStr | Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne |
| title_full_unstemmed | Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne |
| title_short | Urban Green Space Inequity, Socioeconomic Disparities, and Potential Health Implications in Metropolitan Melbourne |
| title_sort | urban green space inequity socioeconomic disparities and potential health implications in metropolitan melbourne |
| topic | environmental justice physical health urban green space planning urban development policy |
| url | https://www.mdpi.com/2076-3417/15/7/3940 |
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