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基于聚类的空间数据可视化方法 被引量：3

Spatial data visualization based on cluster analysis
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摘要 首先介绍了目前空间数据可视化技术的研究内容和基本方法,对基于实体和基于区域两类常用方法进行了分析和总结。在此基础上提出了一种基于聚类的空间数据可视化方法,其基本思想是利用以Delaunay三角网的自适应空间聚类算法(ASCDT)为代表的空间聚类算法进行聚类分析,并获得结果描述参数,结合基本方法和参数特征设计专门用于聚类结果表达的可视化对象,进而实现空间数据的图上投影。最后对该类方法有待进一步探讨和改进的内容进行了展望。 Firstly, the paper introduced the researches and basic methods of spatial data visualization technology, and analyzed two common kinds of methods, namely entity-based and region-based. A clustering-based spatial data visualization method was proposed, which firstly made a cluster analysis of spatial data and got the description parameters of the result through the use of spatial clustering algorithms represented by algorithm ASCDT （ Adaptive Spatial Clustering algorithm based on Delaunay Triangulation）. Secondly, it designed visual objects aimed at the cluster result by combining the basic visualization methods and the characteristics of the parameters. As a result, the mapping relationship was established. Finally, some issues that needed to be further studied and improved were discussed.
作者 张洋 王辰
机构地区 国防科学技术大学信息系统与管理学院
出处 《计算机应用》 CSCD 北大核心 2013年第10期2981-2983,2988,共4页 journal of Computer Applications
关键词 空间数据 空间聚类 Delaunay三角网的自适应空间聚类算法 空间数据可视化 spatial data spatial cluster Adaptive Spatial Clustering algorithm based on Delaunay Triangulation（ASCDT） spatial data visualization
分类号 TP311.131 [自动化与计算机技术—计算机软件与理论]
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参考文献9

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共引文献57

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二级引证文献32

计算机应用
2013年 第10期

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