Taking into consideration the two clustering factors

the mutual distance between clustering objects and the centralizing effects of the higher level objects on the lower

a new clustering method based on minimum cost span tree with control vertexes is proposed. The MST is built based on the power of the clustering objects' mutual distance

and the selecting standard of the splitted edges is controlled by the higher level vertexes. Each splitted edge should be the longest edge under the condition that the two descendant trees must include at least one controlling vertex

and each descendant tree would include one and only one controlling vertex by the end of the algorithm. It has been verified by clustering the data built by ourselves and the earthquake data that this method

with simple input and little intervention

can discover better the true law of data distribution in some cases. To fulfill the needs of data mining

the selecting standard of the controlling vertexes

the 'inconsistent edges' and the efficiency of the algorithm should be improved.