Abstract: Spatial clustering has a significant application value in spatial data mining.In this paper,a novel clustering algorithm DBSB (Density Based Spatial Clustering Method with Heuristically Selecting Border Object) is proposed.The algorithm fastly expands the clusters by a heuristical function to choose core objects in the border region of the known core object,and then merge some clusters by border objects.That is,the DBSB algorithm get the ultimate clustering result through two steps of clustering.Finally,The theoretical analysis and experimental results indicate that the algorithm is effective and efficient.