空间层次聚类显著性判别的重排检验方法

唐建波; 刘启亮; 邓敏; 黄金彩; 蔡建南

doi:10.11947/j.AGCS.2016.20140605

测绘学报 >

2016 , Vol. 45 >Issue 2: 233 - 240

DOI: https://doi.org/10.11947/j.AGCS.2016.20140605

地图学与地理信息

空间层次聚类显著性判别的重排检验方法

唐建波 ,
刘启亮 ,
邓敏 ,
黄金彩 ,
蔡建南

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中南大学地球科学与信息物理学院, 湖南长沙 410083

唐建波(1987-),男,博士生,研究方向为时空数据聚类分析。

收稿日期: 2014-11-19

修回日期: 2015-04-20

网络出版日期: 2016-02-29

基金资助

国家自然科学基金(41471385;41171351);数字制图与国土信息应用工程国家测绘地理信息局重点实验室开放基金(GCWD201401);中南大学中央高校基本科研业务费专项资金(2013zzts247)

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A Permutation Test for Identifying Significant Clusters in Spatial Dataset

TANG Jianbo ,
LIU Qiliang ,
DENG Min ,
HUANG Jincai ,
CAI Jiannan

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School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

Received date: 2014-11-19

Revised date: 2015-04-20

Online published: 2016-02-29

Supported by

The National Natural Science Foundation of China (Nos.41471385;41171351);Open Research Fund Program of Key Laboratory of Digital Mapping and Land Information Application Engineering, NASG(No.GCWD201401);Fundamental Research Funds for the Central Universities of Central South University(No.2013zzts247)

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摘要

同时顾及空间邻近与专题属性相似的空间层次聚类是挖掘空间分布模式的一种有效手段。空间层次聚类方法虽然可以获得多层次的聚集结构,但聚类结果显著性的统计判别依然是一个尚未解决的难题。为此,本文提出了一种空间层次聚类结果显著性的统计判别方法,用于确定空间层次聚类的停止准则,减少聚类过程对参数设置的依赖。通过试验分析与比较发现,该方法能够有效判别空间层次聚类结果的显著性和确定层次聚类合并过程的停止条件,同时具有很好的抗噪性,避免随机结构的干扰。

关键词： 空间层次聚类; 显著性; 空间分布模式; 重排检验

本文引用格式

唐建波 , 刘启亮 , 邓敏 , 黄金彩 , 蔡建南 . 空间层次聚类显著性判别的重排检验方法[J]. 测绘学报, 2016 , 45(2) : 233 -240 . DOI: 10.11947/j.AGCS.2016.20140605

Abstract

Spatial hierarchical clustering methods considering both spatial proximity and attribute similarity play an important role in exploratory spatial data analysis. Although existing methods are able to detect multi-scale homogeneous spatial contiguous clusters, the significance of these clusters cannot be evaluated in an objective way. In this study, a permutation test was developed to determine the significance of clusters discovered by spatial hierarchical clustering methods. Experiments on both simulated and meteorological datasets show that the proposed permutation test is effective for determining significant clustering structures from spatial datasets.

Key words： spatial hierarchical clustering; significance; spatial pattern; permutation test

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