During the COVID-19 pandemic, people have seen the precious value of park green space for health. In the post-COVID-19 Era, it is essential to understand the different needs and expectations of different communities for the use of park green space. A myriad of previous studies focused on the whole city’s demand for park green space, while few studies examined spatial equity from a supply-demand perspective. This paper aims to investigate the differences in park green space accessibility among people of different ages at a community scale. Specifically, to better evaluate the accessibility of park green space and account for the travel choice, we compared the effects of the two-step floating catchment area (2SFCA) method containing different distance decay functions (i.e., the improved 2SFCA methods) by considering the traffic network and the scale of park green space. In addition, we compared the improved 2SFCA methods with the traditional 2SFCA. This study investigated the spatial equity of park green space accessibility in 1184 communities with a total population of 6,468,612 in the central urban districts of Wuhan. The results showed that the high accessible communities were concentrated in the urban center along the Yangtze River. The improved 2SFCA methods outperformed the traditional 2SFCA, and presented smoother gradient information. It was revealed that over half of communities’ park green space accessibility levels did not match their population density. Inequality of accessibility to park green space was found in people of different ages, especially for the youth (Gini coefficient was as high as 0.83). The difference in the accessibility of urban park green space among different age structures implies the need to integrate community green space planning into urban planning in the post-COVID-19 Era.

Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on housing prices in rapidly urbanising regions. Here, we propose a novel methodological framework that integrates the hedonic price model, geographical detector model and the spatial association detector model to understand housing equity issues. The rapidly rising housing prices, vastly transformed urban planning and heterogeneous land use patterns make the urban centre of Wuhan a typical case study. High-value units of public service accessibility are concentrated in built-up areas, while low-value units are located at the urban fringe. The results indicate that larger public services have more significant clustering effects than smaller ones. Recreational, medical, educational and financial facilities all have capitalisation effects on housing prices. Both the geographical detector model and the spatial association detector model could identify the drivers of housing prices, but the explanatory power of the latter is greater and could enhance the validity and reliability of the findings. We further find that the explanatory power of the driving factors on housing prices obtained from the spatial association detector model is greater than that of the geographical detector model. Based on the spatial association detector model, the main drivers of public service facilities are accessibility to restaurants and bars and accessibility to ATMs. In addition, there are bivariate or nonlinear enhancement effects between each pair of driving factors. This approach provides significant insights for urban environmental development planning and local real estate planning.