Abstract

Urban parks have an important impact on the health of urban residents. Normally, the first step is to identify whether the accessibility of urban parks is equitable; however, multiple models that were applied in previous studies have shown different accuracies. In this study, the area within the fifth ring road of Beijing municipality is selected as the location to conduct the accessibility-based equity assessment of urban parks. The urban park accessibility (UPA) of each residential community will be calculated using the Gaussian two-step floating catchment area (G2SFCA) method. Then, random forest regression and partial dependence plots will be carried out to analyze the relationship between UPA and socioeconomic indicators. To identify where the UPA is inequitable, spatial distribution characteristics between the UPA and socioeconomic indicators will be analyzed based on the bivariate treatment of local indicators of spatial association (LISA). The results indicate the close relationships between UPA and four indicators (towns or subdistricts location = LT, bachelor’s degree (or above) = BD, mean house price = HP, and population density = PD). Beijing urban park unfairness exists in low BD with low UPA or low HP with low UPA streets in the southwestern and east areas of Beijing. In addition, unfairness exists in high PD with low UPA streets in the north second to third ring road areas. Therefore, these areas should be prioritized for urban park development. The methods used in this study could be extended to study the relationship between various service facilities accessibility and influencing factors, and the results could guide intervention programs to help reduce urban park inequity.

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Acknowledgments

This work was supported by the National Key R&D Program of China (No. 2016YFC0503304). We would like to thank professor Weiqi Zhou, Dr. Yuguo Qian, Jiahui Ye, Mao Tian and Qingmei Li for their helpful comments.

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 147Issue 3September 2021

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Received: May 29, 2020
Accepted: Dec 22, 2020
Published online: Apr 19, 2021
Published in print: Sep 1, 2021
Discussion open until: Sep 19, 2021

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State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No. 8, Dayangfang, Beiyuan, Beijing 100012, P. R. China. Email: [email protected]
Huiting Yao, Ph.D. [email protected]
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, No. 18, Shuangqinglu, Haidian, Beijing 100085, P. R. China. Email: [email protected]
School of Environment and Nature Resources, Renmin Univ. of China, No. 59, Zhongguancun, Haidian, Beijing 100872, P. R. China. Email: [email protected]
Gang Fu, Ph.D. [email protected]
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No. 8, Dayangfang, Beiyuan, Beijing 100012, P. R. China. Email: [email protected]
Yan Chen, Ph.D. [email protected]
Land Consolidation and Rehabilitation Center, Ministry of Natural Resources, No. 64, Funei, Xicheng, Beijing 100035, P. R. China. Email: [email protected]
Professor, State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No. 8, Dayangfang, Beiyuan, Beijing 100012, P. R. China. ORCID: https://orcid.org/0000-0002-3864-4931. Email: [email protected]
Junsheng Li, Ph.D. [email protected]
Professor, State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No. 8, Dayangfang, Beiyuan, Beijing 100012, P. R. China (corresponding author). Email: [email protected]
Yuanyuan Zhang, Ph.D. [email protected]
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No. 8, Dayangfang, Beiyuan, Beijing 100012, P. R. China. Email: [email protected]

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