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.
Highlights
In recent years, the use of urban mass data to analyze the spatial structure of cities has provided a new research
The use of urban mass data to analyze the spatial structure of cities has provided a new research Journal of Advanced Transportation paradigm for the sustainable development of cities. e use of a wider range of urban data includes rail transit card data, mobile phone signaling data, network review data, thermal map data, microblogging sign-in data, and night lighting data
Based on the open source data POI (Point of Interest), it provides an accurate and effective alternative to urban research. e POI data is an expression of a virtual abstraction of a real geographical entity in space, has spatial attribute information, has a large amount of data, and is easy to acquire
Summary
The use of urban mass data to analyze the spatial structure of cities has provided a new research. E POI data is an expression of a virtual abstraction of a real geographical entity in space, has spatial attribute information, has a large amount of data, and is easy to acquire It is one of the most important data in the study of urban geography. In Guiyang’s urban sustainable development strategy, the development concept of building a multicenter city is mentioned, and the spatial structure layout of the city’s multicenter is formed To this end, this study uses the POI data of Guiyang City from 2016 to 2018, taking the main city of Guiyang as an example and using the nuclear density analysis and spatial correlation index in geography to analyze the evolution characteristics of urban centers in the main urban area of Guiyang. Big data are used to simulate the urban spatial structure to achieve the purpose of exploring the urban spatial form of Guiyang, the capital city of western China. Further explore the sustainable development model of urban spatial structure
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