地理信息科学

多尺度空间单元区域划分方法

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  • 1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101;
    2. 香港中文大学地理系;
    3. 西安交通大学信息与系统科学研究所, 西安 710049
骆剑承 (1970- ), 男, 博士, 副研究员。主要从事时空数据处理与分析和数据挖掘研究。发表论文30余篇。E-mail: luojc@lreis.ac.cn

收稿日期: 2001-05-01

  修回日期: 2001-11-20

  网络出版日期: 2002-03-25

基金资助

国家自然科学基金项目 (40101021), 中科院地理科学与资源研究所知识创新项目(CXIOG-D00-06)

Scale-Space Theory Based Regionalization for Spatial Cells

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  • 1. LREIS, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Department of Geography, The Chinese University of Hong Kong;
    3. Institute for Information and System Sciences, Faculty of Science, Xi'an Jiaotong University, Xi'an 710049, China

Received date: 2001-05-01

  Revised date: 2001-11-20

  Online published: 2002-03-25

Supported by

National Natural Science Foundation of China, No. 40101021; Knowledge Innovation Project of IGSNRR, CAS. No. CXIOG-D00-06

摘要

传统空间单元的区域划分通常仅以属性数据作为划分依据,而对单元之间空间依赖关系考虑不周。在尺度空间理论基础上,提出多尺度空间单元区域划分方法,在考虑空间单元属性信息的同时,增加了空间单元的相互依赖关系,使得在空间尺度在由小变大过程中,具有高度空间相互依赖关系的空间单元相互融合,得到不同空间尺度下的区域划分。以江苏省从1978年到1995年的18年社会经济发展数据为基础,进行了全省社会经济发展水平的区域划分的试验,结果表明与实际发展水平的分布情况相吻合。

本文引用格式

骆剑承, 周成虎, 梁怡, 张讲社,黄叶芳 . 多尺度空间单元区域划分方法[J]. 地理学报, 2002 , 57(2) : 167 -173 . DOI: 10.11821/xb200202006

Abstract

Traditional regional partitioning model for spatial cells is only built upon the information of attributes in every cell. However, the spatial relationships and their spatial interaction between cells are not considered sufficiently. In this study, based on scale-space theory a new approach for regional partitioning or regionalization for spatial cells is proposed so that the elements of spatial relationship between cells could be integrated besides considering the information of attributes. By this approach, regional partitioning in multiple scale can be accomplished on the basis of the spatial clustering algorithm that at certain scale the spatial cells could be melted into one class if their connective direction is the same within the road transformation system that is built upon by a spatial interactive model. Finally, according to the social and economic statistical data of 18 years from 1978 to 1995, the experiments of regional partitioning for social and economic development level of Jiangsu Province are achieved. In the experiments, despite only the simple spatial correlative model is used as the spatial interactive model for the scale-space clustering algorithm the regional partitioning results are highly accordant with real situations.

参考文献


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