Research on the Spatial and Temporal Distribution Evolution and Sustainable Development Mechanism of Smart Health and Elderly Care Demonstration Bases Based on GIS

Utilizing GIS technology and spatial analysis methodologies, this study endeavours to delve into and grasp the localized attributes of the regional units under investigation from a geographical vantage point, as well as the interrelationships among these units. This endeavour encompasses the identification and quantification of developmental patterns, the assessment of trends, and the resolution of any intricate issues about geographical location to make prognostications and informed decisions. Classic spatial analysis techniques such as the geographic concentration index, kernel density analysis, Thiessen polygons, and spatial autocorrelation analysis (Moran’s I index) are employed in this inquiry. Initially, the study utilized the nearest neighbour index and geographic concentration index to gauge the equilibrium, proximity, and concentration of the spatiotemporal distribution of smart health elderly care demonstration bases across 31 provinces in China. Upon confirming the spatial clustering and imbalance of the distribution of elderly care demonstration bases in China, kernel density analysis was applied to compute the density of point features surrounding each output raster cell and to visually represent the spatiotemporal distribution status of the bases. Finally, Thiessen polygons and spatial autocorrelation analysis (Moran’s I index) were introduced to further elucidate and validate the spatial distribution patterns of the elderly care demonstration bases. The findings of the research reveal that smart health and elderly care bases in China manifest spatial clustering, predominantly concentrated in the central and eastern regions of the country. The overarching pattern embodies a spatial model characterized by a “concentration in three poles with multiple cores surrounding”. Ultimately, the study offers recommendations for the nexus between three principal mechanisms: market-driven development mechanisms, policy-driven development mechanisms, and technology-driven development mechanisms, advocating for the further progression of intelligent construction to attain the sustainable development of demonstration bases. This research furnishes a scientific foundation for the planning and industrial advancement of pertinent departments.