Analysis of Equity and Accessibility in Urban Green Space Using G2SFCA, sDNA, and K-mean Clustering Methods – A Case Study of Foshan, China
Green space serves many functions required for urban development and is a significant part of urban ecology. This study discusses the accessibility relationship between the supply and demand for park green space in Foshan by using a novel schema that combines G2SFCA, sDNA, and K-mean Clustering Methods. The results indicate that the accessibility of park green space is subpar; there are significant issues with local green space supply and demand, and the accessibility index declines from the outer to the inner edge. High accessibility zones disperse around the periphery, including Nanshan, Datang, and Yanghe towns, and their spatial distribution is undoubtedly discrete. The primary metropolitan districts as Dali Town, Southwest Street, Hecheng Street, Xiqiao Town, etc., are generally where the locations with accessibility near to the average distributed. These areas have an aggregation tendency in their spatial distribution and extend outward along the edge of green regions. The less accessible neighborhoods share boundaries with the Chancheng District’s urban core along Zhangchu Street, Zumiao Street, Shiwan Street, and Guicheng Street, clearly exhibiting the features of spatial aggregation. Utilizing reconstructing aging urban areas and enhancing urban road systems, Foshan will be able to hasten the creation of park cities.
KEYWORDS: Gaussian Two-step Floating Catchment Area Method (G2SFCA); Urban Green Space; Accessibility Analysis; sDNA (spatial Design Network Analysis); K -mean clustering