A Study on The Distribution of Various Production and Living Facilities in The Main Urban Area of Xining Based on POI Data

This study explores the distribution patterns of production and living facilities in the main urban area of Xining based on POI data. The research background focuses on the unique geographical constraints of Xining, a typical plateau valley city, which result in uneven facility distribution during the urbanization process, affecting residents' quality of life and urban operational efficiency. The high spatial precision of POI data provides a microscopic analytical perspective for this research. The significance of the study lies in filling the gap in research on the spatial structure of service facilities in plateau cities and responding to the call of the UN Sustainable Development Goals (SDG 11) for inclusive cities. The research objective is to reveal the multi-dimensional polarization characteristics of POIs in the service industry and their formation mechanisms through geospatial analysis, thereby providing a basis for optimizing urban planning and enhancing social equity. Methodologically, the kernel density estimation technique is primarily employed to quantify the spatial agglomeration intensity of eight types of facilities and identify hot spot distributions. This method integrates multi-type POI data to intuitively present the patterns of functional superposition and differentiation. The analysis results indicate that the facility distribution exhibits significant "core-periphery" polarization: Educational facilities show a three-level diffusion pattern with the old urban area as the coret. Automotive services form a dual-center layout. Other living facilities, such as catering establishments and shopping centers, display a multi-core distribution; public toilets and bus stops present axial radiation, but their coverage in old communities is insufficient. The conclusion points out that the polarization mechanisms are dominated by topographic constraints, policies (e.g., educational parks), and transportation networks.