Research on accessibility analysis of park green space based on big data: taking Xiongan New Area in China as an example

Park green spaces are an important part of urban ecosystems, promoting urban livability and improving residents’ well-being. The rational spatial distribution of park green spaces promotes equitable and healthy urban development. Accessibility studies of park green space are essential for measuring its spatial distribution and evaluating the effectiveness of its ecological services. Based on open-source network big data such as POI and vector road network data, this study uses ArcGIS network analysis to analyze the accessibility of park green spaces in Xiongan New Area under three modes of transportation: walking, cycling and driving. It shows that the park green space resources in Xiongan New Area are lacking at this stage, and there are blind spots for park green space services in individual areas. The accessibility ratio is less than 20% under walking and cycling modes, while the accessibility ratio is better under driving mode, reaching 92.46% within 15 min. The optimization strategy is further proposed with the data analysis to provide a theoretical basis for the green space planning and design of Xiongan New Area.