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

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.