A delicacy evaluation method for park walkability considering multidimensional quality heterogeneity

In the post-pandemic era, park walkability plays a vital role in promoting residents' physical and mental health in all aging societies. In current walkability calculation methods, the number of indicators reflecting park quality is limited, and the data resolution is too low to capture accurate park demand patterns. Moreover, the travel impedance based on the ArcGIS network cannot reveal the impedance differences between distinct road types. Therefore, a delicacy evaluation method for park walkability that considers multidimensional quality heterogeneity is required. Taking a residential compound as the unit, this study evaluated park walkability based on multi-source big data using the Huff-based Ga2SFCA (Gaussian two-step floating catchment area) model. The results suggest that, considering multidimensional quality heterogeneity, this method can accurately quantify the influence of facility improvement on park walkability, better describing the supply and demand relationship. Although the perfection of facilities can effectively improve park walkability, its influence on park distribution equity is small. To reduce the disparity in park distribution, the construction of new parks is necessary. A “pocket park” is a good option considering the limited land resource. Open campuses are good alternatives. Therefore, as an epidemic prevention policy, the “shut down policy” of campuses to the public does great harm to park walkability and the resulting equity, stopping the spillover of positive externalities of universities and colleges. This research not only improves the 2SFCA method from the indicator abundance and indicator counting approach in the supply dimension but also improves studies on park accessibility in terms of data accuracy and data resolution. This has important theoretical and practical significance for the delicacy management of urban areas.