Accessibility Analysis of Urban Park Green Spaces in Nanning City Based on Network Analysis and G2SFCA

Abstract

The accessibility of urban park green spaces holds significant importance for the daily lives of city dwellers and for evaluating urban liveability. This study integrates the Gaussian two-step floating catchment area method (G2SFCA) and network analysis to assess the accessibility distribution characteristics of park green spaces in Nanning City. The G2SFCA accounts for population density and park area to quantify per capita service capacity, while network analysis simulates real transport networks to evaluate distance- based and time-based accessibility. Results indicate significant disparities in accessibility across Nanning's districts: Qingxiu and Liangqing District exhibit the highest accessibility with average proportions of 65.84% and 45.54% respectively, while Xixiangtang and Xingning District record the lowest at 18.01% and 16.61%. Spatial Autocorrelation Analysis (Moran’s I = 0.928) further indicates pronounced clustering, with high–high clusters concentrated in the southeast and low–low clusters in the northern and western areas. The comparative analysis highlights the methodological complementarity between supply–demand based and distance–cost based evaluations, providing a more robust understanding of green space accessibility. Policy recommendations suggest prioritising the addition of community parks and green corridors in low-accessibility and high-density areas such as northern Xixiangtang and western Jiangnan, while consolidating the “large core–small node” layout along the Yongjiang River. This research offers scientific support for ecological spatial planning and contributes to advancing the development of a liveable and sustainable urban environment in Nanning.