Accessibility of Healthcare Resources to Public Housing in Shenzhen, China: Indirect Map Service and Optimized Two-Step Floating Catchment Area Method

In China, the equal accessibility of social infrastructure, especially public housing and healthcare, has become a prominent concern in solving the problems of rapid but uneven growth-oriented urbanization in the post-reform era. However, few studies have focused on the accessibility of various healthcare resources to different types of public housing using different transport modes. Utilizing Internet map services, this study first calculated the travel time from talent, economically affordable, and public rental housing to hospitals using three transport modes—walking, public transport, and driving—in Shenzhen, China. Subsequently, the optimized two-step floating catchment area method (2SFCA) was employed to comprehensively evaluate the accessibility of healthcare resources to public housing and explore differences in healthcare accessibility among different populations. The results reveal that: (1) Public housing is located far away from healthcare resources, with 15% of public housing unable to access AAA hospitals within 30 minutes by car, and only 10% able to access ordinary hospitals within 15 minutes. (2) Accessibility of healthcare resources to public housing exhibits spatial heterogeneity, gradually declining from special to non-special economic zones. (3) Talent housing experiences the best accessibility, followed by affordable and public rental housing. (4) Public transportation and walking exhibit greater spatial variation in accessibility than driving. Theoretically, the current public housing accessibility in Shenzhen reflects the common problems of public housing accessibility throughout the country. In the process of promoting the equal accessibility of basic public services, focus on its accessibility should be emphasized. This study proposes an optimized 2SFCA by introducing a Gaussian distance decay function, establishing a multilevel search radius, considering supply and demand-side competition effects, and using real-time traffic big data. Our methodological framework simultaneously considers differences among various types of public housing, hospitals with different service capacities, and diverse travel modes. This provides a new research perspective for a comprehensive and thorough understanding of the equal accessibility of basic public services.