General multidimensional cloud model and its application on spatial clustering in Zhanjiang, Guangdong

Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial ob...

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Bibliographic Details
Published in:Journal of geographical sciences Vol. 20; no. 5; pp. 787 - 798
Main Authors: Deng, Yu, Liu, Shenghe, Zhang, Wenting, Wang, Li, Wang, Jianghao
Format: Journal Article
Language:English
Published: Heidelberg SP Science China Press 01.10.2010
Springer Nature B.V
Graduate University of Chinese Academy of Sciences, Beijing 100049, China
Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
Graduate University of Chinese Academy of Sciences,Beijing 100049, China%Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China%School of Resources and Environment Science, Wuhan University, Wuhan 430079, China%Institute of Policy and Management, CAS, Beijing 100080, China
Subjects:
Bgi / Prodig
Comparative studies
Earth and Environmental Science
General methodology
Geographical Information Systems/Cartography
Geography
Nature Conservation
Physical Geography
Remote Sensing/Photogrammetry
Spatial distribution
Statistical and stochastic methods
云模型
空间对象
空间相互作用
空间聚类
Guangdong
China
Zhanjiang
multi-dimensional cloud
membership degree
spatial clustering
data mining
Cluster analysis
Spatial analysis
Infrastructure
Educational establishment
Land
Land value
ISSN:1009-637X, 1861-9568
Online Access:Get full text
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Description
Summary:Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures＇ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated char- acteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.
Bibliography:Zhanjiang
multi-dimensional cloud
membership degree
spatial clustering
data mining
multi-dimensional cloud; spatial clustering; data mining; membership degree; Zhanjiang
11-4546/P
TP311.13
P208
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1009-637X
1861-9568
DOI:10.1007/s11442-010-0811-8