The method of object-oriented classification for remote sensing images, based on image segmentation which could create objects sets of homogeneous pixels, provides a way to analyze object's features, such as spectral, shape, topology, texture and so on, and to realize the functions of discriminating various species and automatic classification. The traditional way of analyzing and extracting urban vegetation community was taken as a reference, a new classification method has been developed using QuickBird satellite image in Shanghai. With the new method, the total precision is 84.4%, 24.4% higher than conventional supervised classification. The principle of the new approach mentioned may be useful as a new algorithm joined with existing classifiers.