一种基于相交关系的GML空间聚类算法

A Spatial Clustering Algorithm Based on Intersection Relation for GML Data

提出一种基于相交关系的GML空间聚类算法SCIR,该算法以GML数据作为数据源,计算空间对象的相交关系,针对空间对象的相交关系和非空间属性,定义了一种相似度度量方法,利用ROCK算法进行聚类。实验结果表明,算法SCIR能实现GML数据中基于相交关系的空间对象聚类,并具有较高的效率。

Algorithm SCIR for spatial clustering based on intersection relation is proposed. The algorithm computes intersection relations between spatial objects for GML data. The similarity between spatial objects is defined by intersection relations and non-spatial attributes of spatial objects. Spatial objects are clustered using algorithm ROCK. The experimental results show that algorithm SCIR is effective and efficient.