娱乐
环境规划
透视图(图形)
环境质量
衡平法
地理
质量(理念)
环境资源管理
业务
环境保护
环境科学
生态学
政治学
生物
计算机科学
认识论
哲学
人工智能
法学
作者
Ru Guo,Jessica Ann Diehl,Ran Zhang,Hongcheng Wang
标识
DOI:10.1016/j.landurbplan.2024.105065
摘要
Spatial equity in urban park recreational services can significantly contribute to sustainable urban planning. However, there are shortcomings in research comparing the spatial equity of different categories of parks and urban parks overall from the perspective of recreational opportunities and recreational environment quality available to residents across various neighborhoods. In this paper, emphasizing park access within a 10-minute walk, we proposed an evaluation system at the neighborhood level for regional parks, community parks, and urban parks overall (regional and community parks combined) from this under-researched perspective. Taking Singapore as a case study, the feasibility of this evaluation system has been verified. We applied Lorenz curve, Gini coefficient, locational entropy, and spatial autocorrelation analysis to compare the differences of horizontal spatial equity and spatial distribution patterns of different categories of parks and urban parks overall from the perspective of recreational opportunities and recreational environment quality. Results showed that the horizontal spatial inequity of recreational opportunities is higher than that of recreational environment quality with respect to regional parks, community parks, and urban parks overall. Compared with regional parks, community parks have a greater effect on improving the horizontal spatial equity of recreational opportunities and recreational environment quality of urban parks overall. Park recreational opportunities and recreational environment quality available to residents in each neighborhood have significant spatial accumulation patterns. The evaluation system and its application enable a more comprehensive assessment of the spatial distribution of neighborhood-level park recreational opportunities and recreational environment quality.
科研通智能强力驱动
Strongly Powered by AbleSci AI