Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining

被引:0
|
作者
Zhao, Haijuan [1 ,2 ]
Long, Yan [3 ]
Wang, Nina [4 ]
Luo, Shiqi [1 ]
Liu, Xi [1 ]
Luo, Tianyue [5 ]
Wang, Guoen [1 ]
Liu, Xuejun [1 ,6 ]
机构
[1] Wuhan Univ, Sch Urban Design, Wuhan 430072, Peoples R China
[2] Wuhan Design Consultat Grp Co Ltd, Wuhan 430023, Peoples R China
[3] Wuhan Univ Sci & Technol, Sch Art & Design, Wuhan 430065, Peoples R China
[4] Cornell Univ, Sch Appl Informat Syst, 2 West Loop Rd, New York, NY 10044 USA
[5] Wuhan Transportat Dev Strategy Inst, Wuhan Planning & Design Inst, Wuhan 430010, Peoples R China
[6] Wuhan Univ, Res Ctr Digital City, Wuhan 430072, Peoples R China
关键词
urban hot spots; spatio-temporal pattern mining; space-time cube; bivariate Moran's index; disorderly multivariate logistic regression model; DYNAMICS;
D O I
10.3390/ijgi13060186
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban-rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan's new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran's index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities.
引用
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页数:34
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