地理科学 ›› 2003, Vol. 23 ›› Issue (1): 66-71.doi: 10.13249/j.cnki.sgs.2003.01.66

• 论文 • 上一篇    下一篇

多元统计分析在分区研究中的应用

王秀红   

  1. 中国科学院地理科学与资源研究所, 北京 100101
  • 收稿日期:2002-02-27 修回日期:2002-05-20 出版日期:2003-01-20 发布日期:2003-01-20
  • 基金资助:
    国家科技攻关项目(2002BA517A11-7);中国科学院创新项目(CXIOG-A00-03-01)资助。

Application of Multivariate Statistical Analysis in Regionalization Study

WANG Xiu-Hong   

  1. Institute of Geographical Sciences and Natural Resources Research, the Chinese Academy of Sciences, Beijing 100101
  • Received:2002-02-27 Revised:2002-05-20 Online:2003-01-20 Published:2003-01-20

摘要: 探讨了基于因子分析的聚类分析方法在遵循主要地理区划原则,特别是综合分析与主导因素相结合的原则和相对一致性原则过程中的特色。以中国土地利用程度和效益分区为例,首先利用因子分析对评价指标进行了降维处理,并研究了各个评价指标之间的关系;然后利用聚类分析,结合主要区划原则,将全国划分为5个类型区,12个亚区。

Abstract: Various types of indices commonly used to illuminate the properties of evaluated unit just reflected its situation from a few of the sides; therefore, simple using of these indices to proceed mathematical analyses and to do regionalization research would usually deviate from the right direction. Taking the basic principles for regionalization as a directing framework, the use of mathematical method would be more reasonable, apart from getting more typical and exacter data. The use of classical principles for regionalization in mathematical analyses is helpful to the selection of evaluated unit, as well as explanation of the result of mathematical analyses. Cluster analysis based on factor analysis could carry out some principles for regionalization, such as the linking of integrated analysis with dominant factor, comparative consistency, and conjugate. The rational use of mentioned method would improve the regionalization study. By using the mentioned principles and multivariate statistical analysis, selecting 30 provinces, autonomous regions and municipalities as evaluated units, China could be divided into 5 regions and 12 sub-regions concerning its land use degree and benefit.

中图分类号: 

  • P323.1