The invention discloses a remote sensing image fuzzy multi-center supervised classification method and application, and the method comprises the steps: firstly segmenting an image into particles with similar sizes in a spectral space through employing a hierarchical clustering method based on an FCM method, and then carrying out the marking and classification of the particles through employing a marking sample, and dividing the particles into three types: pure particles, impure particles, and unmarked particles, wherein the center of each pure particle represents a spectrum center of each land coverage type, the spectrum diversity of each land coverage type is represented by the centers, and the centers of each type are stored by a coverage tree; and thirdly, determining the membership degree of each unmarked sample belonging to each land coverage type by the nearest pure particles. Experimental results show that the supervised classification method realizes multi-center expression of complex remote sensing data, describes diversity of remote sensing data spectrums, and further improves precision and reliability of remote sensing classification.