Research on the Simulation Application of Data Mining in Urban Spatial Structure

Abstract

Data mining and simulation of the Internet of things (IOT) have been applied more and more widely in the rapidly developing urban research discipline. Urban spatial structure is an important field that needs to be explored in the sustainable urban development, while data mining is relatively rare in the research of urban spatial structure. In this study, 705,747 POI (Point of Interest) were used to conduct simulation analysis of western cities in China by mining the data of online maps. Through kernel density analysis and spatial correlation index, the distribution and aggregation characteristics of different types of POI data in urban space were analyzed and the spatial analysis and correlation characteristics among different functional centers of the city were obtained. The spatial structure of the city is characterized by “multicenters and multigroups”, and the distribution of multicenters is also shown in cities with different functional types. The development degree of different urban centers varies significantly, but most of them are still in their infancy. Data mining of Internet of things (IOT) has good adaptability in city simulation and will play an important role in urban research in the future.