using unmixing methods to classify lithological and alteration units based on hyperspectral images

expensive to provide these maps  with field measurements  therefore  it is better to use new methods. this study provides a lithological and alteration mapping units with dominant minerals based on hyperspectral images of eo1-hyperion satellite. to do so, two different zones  were  investigated:  the  cuprite-nevada  and  mozahem  volcano  in  iran  which  have suitable conditions for our study. five methods with different structures  have been used: sam, ace, cem, osp, and lsu  to evaluate their  ability  of  geological unit  separation. the results show that the differences and separability level in spectral signatures of training data are main factors in affecting the results in covariance base methods  but  it is low in the linear methods. this study revealed the accuracy of 86.45% for lsu in mineral mapping of cuprite area and 69.54% for ace in alteration mapping for mozahem volcano which displays more efficiency than the other methods.