By actively adapting urban planning to identified social needs, residential areas tend to be more people-oriented, fairer, resource-saving, and sustainable. The emergence of big data has provided new opportunities for the planning of residential urban areas. Since the quantity and age-appropriateness of neighborhood facilities are important criteria when developing the ideal neighborhood, this study investigated the associations of the number of neighborhood facilities and the age groups within those neighborhoods by using the Wuhan metropolitan area in China as a case study and by applying a Geodetector and regression analysis to points-of-interest data. In terms of age groups, the neighborhood facilities of kindergartens, pharmacies, and bus stations were found to be highly associated with population size, regardless of the age difference. It was also found that convenience stores were closely related to the adult population, and that convenience stores, community hospitals or clinics, and vegetable markets or fresh supermarkets were associated with the elderly population. Facilities without significant correlations were equally important, but it was found that there was no statistical correlation between the number of facilities and the distribution of the population. The weak association of key educational resources and medical resources with the population indicates a concentrated distribution of educational resources and medical resources, and the latent insufficiency of schools, community hospitals, or clinics at some neighborhoods. It concludes that planning of neighborhood facilities for residential areas in Wuhan requires optimization in terms of matching the provision of facilities with population size and social structure. Furthermore, more efforts should be put into supplementing important facilities and building differentiated residential area programs based on age structure.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited