A Novel Spatial Clustering Algorithm Based on Spatial Adjacent Relation for GML Data

被引：0
|
作者：
Ji, Genlin [1 ]
Miao, Jianxin [1 ]
Yang, Ming [1 ]
机构：
[1] Nanjing Normal Univ, Dept Comp, Nanjing 210097, Peoples R China
来源：
PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL I | 2009年
关键词：
GML; spatial clustering; spatial adjacent relations;
D O I：
10.1109/ETCS.2009.69
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
With the development of WEBGIS, GML is becoming a common way of storing spatial data. GML is an application of XML in geographic information system. In this paper, a novel algorithm SCAR-GML is proposed for spatial clustering in GML data. Compared with other spatial clustering algorithms, SCAR-GML clusters spatial objects based on the spatial adjacent relations, while the reported algorithms like DBSCAN just cluster the spatial objects that are near to each other into a cluster. SCAR-GML firstly computes the spatial adjacent relations and then clusters the objects according to the computed relations. The objects in one cluster may not be near to each other, but they have similarity in the spatial adjacent relations. Encouraging simulation results are observed and reported. The experiment shows that SCAR-GML is effective and efficient.
引用
收藏
页码：278 / 282
页数：5
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