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Due to the close links between quality of life standards and level of regional development, it is important to gain an improved understanding of the factors that contribute to unequal spatial accessibility of medical and health services in China. This study analyzed 2859 counties using the average shortest distance traveled from settlements to medical facilities to calculate spatial accessibility. The Theil index at three levels (three partitions, eight economic zones and provinces) was used to assess the inequality between regions. Then, a method of spatial autocorrelation was used to assess the spatial agglomeration characteristics of spatial accessibility. To explore the underlying reasons for the imbalance in spatial accessibility, a total of eight indicators in three aspects (nature, society, and economy) were collected and geographically weighted regression (GWR) was employed to investigate spatial heterogeneity. We observed marked disparities in spatial accessibility to medical facilities at the national level. In particular, there appears to be improved spatial accessibility and lesser regional inequality in eastern and central regions as opposed to western Chinese regions; in coastal regions instead of inland regions; and in municipalities such as Beijing, Tianjin, and Shanghai, but not in other provinces and autonomous regions. Besides, significant global autocorrelation and obvious clusters were revealed in a spatial pattern analysis. A wide range of hot-spot areas (clusters of poor spatial accessibility) mainly concentrated in Tibet and other areas with complex terrain and lagging social and economic development. A number of cold-spot areas (clusters of good spatial accessibility) mostly scattered in built-up areas especially municipalities and well-developed urban agglomeration such as the Yangtze River Delta, the Pearl River Delta, and the Wuhan 1 + 8 city circle. Furthermore, the relationships between influencing factors and spatial accessibility were also investigated. The influence of altitude on spatial accessibility gradually decreased from the West to the East, while the influence of slope decreased from the South to the North with prominent provinces of Qinghai and Gansu. Population density exerted a higher impact on the distance in the southwest region whereas the urbanization rate influenced the northeast and southeast coastal region more intensively. In contrast, the pattern of educational level was relatively discrete. The influencing pattern of economic factors in both per area GDP and tertiary industry output share of accessibility showed apparent regional characteristics in the southeast coastal areas, as well as in the northwestern and northeastern parts. Outcomes from this study can be used to provide important information to aid policy making, while also facilitating future research aimed at improving the understanding of equality and sustainable development of medical facilities.

Spatial patterns of urban expansion mainly include infilling, edge expansion, and outlying growth patterns. The cellular automata (CA) model, is an important spatio-temporal dynamic model and effectively simulates infilling and edge-expansion urban expansion. but is evidently lacking in outlying scenarios. In addition, CA cannot explain the causes and processes of urban land expansion. Given these limitations, we proposed a novel urban expansion model called simulation model of different urban growth pattern (SMDUGP), which can work well in both adjacent (i.e., infilling and edge expansion) and outlying growth patterns. SMDUGP has two main components. First, we divided the non-urban region into two categories, namely, candidate region for adjacent pattern urban growth (CRFAP) and candidate region for outlying pattern urban growth (CRFOP). Second, different methods were utilized to simulate urban expansion in the different categories. In CRFAP, a CA model based on the potential of urban growth was proposed to simulate urban growth in relatively randomly selected urban growth regions based on the discrete selection model and Monte Carlo method as the expansion area was implemented in CRFOP. Huangpi, a suburban area in Wuhan, is utilized as the case study area to simulate the spatial and temporal dynamics of urban growth from 2004 to 2024. SMDUGP can effectively simulate outlying urban growth with a highly improved simulation precision compared with the traditional CA model and can explain the causes and processes of urban land expansion.