Integrating Spatial and Attribute Characteristics of Extended Voronoi Diagrams in Spatial Patterning Research: A Case Study of Wuhan City in China

被引:5
|
作者
Miao, Zuohua [1 ]
Chen, Yong [1 ]
Zeng, Xiangyang [1 ]
Li, Jun [1 ]
机构
[1] Wuhan Univ Sci & Technol, Sch Resources & Environm Engn, 947 Heping Rd, Wuhan 430081, Peoples R China
基金
湖北省教育厅重点项目; 中国国家自然科学基金;
关键词
geospatial proximity; attribute similarity; generalized Euclidean distance; Voronoi diagrams; spatial pattern; LAND-USE CHANGE; CENTRAL PLACE THEORY; URBAN SPRAWL; LANDSCAPE PATTERN; CELLULAR-AUTOMATA; LOCAL INDICATORS; GROWTH; SIMULATION; DYNAMICS; MODELS;
D O I
10.3390/ijgi5070120
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Rapid urbanization has caused numerous problems, and the urban spatial structure has been a hot topic in sustainable development management. Urban spatial structure is affected by a series of factors. Thus, the research model should synthetically consider the spatial and non-spatial relationship of every element. Here, we propose an extended Voronoi diagram for exploring the urban land spatial pattern. In essence, we first used a principal component analysis method to construct attribute evaluation indicators and obtained the attribute distance for each indicator. Second, we integrated spatial and attribute distances to extend the comparison distance for Voronoi diagrams, and then, we constructed the Voronoi aggregative homogeneous map of the study area. Finally, we make a spatial autocorrelation analysis by using GeoDA and SPSS software. Results show that: (1) the residential land cover aggregation is not significant, but spatial diffusion is obvious; (2) the commercial land cover aggregation is considerable; and (3) the spatial agglomeration degree of the industrial land cover is increased and mainly located in urban fringes. According to the neo-Marxist theory, we briefly analyzed the driving forces for shaping the urban spatial structure. To summarize, our approach yields important insights into the urban spatial structure characterized by attribute similarity with geospatial proximity, which contributes to a better understanding of the urban growth mechanism. In addition, it explicitly identifies ongoing urban transformations, potentially supporting the planning for sustainable urban land use and protection.
引用
收藏
页数:19
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