Abstract: Remote sensing data are discrete, finite and nonlinear. On the basis of the analysis and extraction of thematic texture information, using the grey levels of the abnormal areas and the orecontrolling structure information as the characteristic values, the authors have constructed a statistical identification model based on statistical theory for classing the characteristic vectors of unknown area. It has been applied in the Xiaoxinancha of east Jilin multivariable metallogenic target forecast and the prospecting and assessment near mining area. Combining extracted altered information with mine engineering geological knowledge, it well shows coppergold mineralization and the results tallies with fact proved by exploring mineral engineering in the field.

Key words: remote sensing, altered information, statistical identification model