Abstract Body

With an increasing attention to the equity in public natural resource distribution, the accessibility of urban parks highlights the standard of access by proximity for building socially just ecocity. Integrating related factors, such as path, land use, income and ethnicity, recent studies have been improved with the transformation of methods from the questionnaire-based qualitative to the GIS-based quantitative. However, in the process of urban planning, the deficiency analysis of park green space distribution mostly based on the simple buffer by bird path could result in a greater assessment error. In this case study, facilitated by the multi-source big data, more specific characteristics of the spatial distribution of urban residents were identified. The improved two-step floating catchment area (2SFCA) method was employed in combined with the network analyst in ArcGIS to evaluate the actual accessibility of park green spaces in Wuxi City, China. The urban districts with low accessibility to park green spaces were mapped as the key areas for equity promotion. Compared with the traditional methods, the spatial fitting degree between service capacity of urban park green spaces and users’ demand was measured more accurately. The study could conduct the layout optimization of urban park green spaces effectively.