Community-Level Urban Green Space Equity Evaluation Based on Spatial Design Network Analysis (sDNA): A Case Study of Central Wuhan, China

Abstract

Urban green spaces (UGSs) provide numerous irreplaceable environmental and social benefits to humankind, but the lack of baseline information makes it difficult to propose a reasonable greening strategy so as to achieve an equitable allocation of community green spaces. This paper divides UGSs into three classes using the spatial design network analysis (sDNA) and quantifies the UGS accessibility of communities in central Wuhan. Based on these results and the Gini coefficient, we analyze the UGS equity of the spatial distribution at the community level, then propose future greening strategies both at the city and community levels. The results show that the railway station and old Wuhan city are the core areas of traffic network strength (TNS). UGSs are evenly distributed in the core areas of TNS, but the number of UGSs in non-core areas is small, and their distribution is relatively uneven, and the number of communities with medium UGS accessibility is the largest, carrying the densest residential population. Most communities perform well in terms of UGS equity, but the UGS equity of 163 communities, covering a population of more than one million, remains to be improved. The method and conclusions of this study will contribute to the future greening policy making of 965 communities in central Wuhan, thus promoting the orderly planning and high-quality construction of community living circles.

Mismatch between infrastructure supply and demand within a 15-minute living circle evaluation in Fuzhou, China

“…The kernel density method is a commonly used method that directly reflects the density of point data distribution in a certain range, and can reflect the relative concentration of point data. It is widely used in the layout description of spatial point data [ 16 ]. In this paper, the poi point data of 14 kinds of infrastructures acquired in the main urban area of Fuzhou City at the end of 2021 were selected for kernel density analysis.…”

Study on Spatial-Temporal Change of Urban Green Space in Yangtze River Economic Belt and Its Driving Mechanism

“…The Gini index is used to evaluate the fairness of social resources distribution, such as measuring the fairness of public transportation service, medical resources, and mineral resources distribution [ 47 ]. The Gini index of green space distribution can accurately reflect the uniformity and fairness of green space distribution in a specific region [ 48 , 49 ]. Its value ranges from 0 to 1.…”

Distribution patterns and drivers of urban green space and plant diversity in Haikou, China

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