Abstract: Based on the theory of dynamical clustering,an improved iterative clustering algorithm was brought forward.This iterative clustering algorithm realized on the Microsoft Visual C++ platform by judging the threshold of distance between classes,and had following advantages,such as did not need to predefine initial clustering centers,reduced number of initial parameters to be decided before the classifying,guaranteed more realistic classifying results and made the clustering process easier.In order to validate the practicability of this algorithm,the South Liaoning Province was chosen as a study area,and the moderate resolution satellite data of 250m TERRA MODIS and 250m MERSI of FY3A satellite were used to compared with ISODATA algorithm.The results indicated that the classifying precision of new arithmetic was better,and could be used in classifying remote sensing data.

Key words: Clustering, Clustering, Iterative, MODIS, MERSI