Separation of Carbonates by Using PCA on ASTER Bands  Figure (a): Geological map of this case study Applying PCA Analysis in order to Separate Carbonates As discussed before, dolomite has an important role in mineralization and in some areas, dolomite is mixed by limestone, therefore in order to separate Carbonates into limestone and dolomite, PCA analysis was applied. The benefit of this method is omitting Albedo and topography shadows from the images. PCA was applied to subsets of four ASTER bands, using an adaptation of the Cro´sta technique proposed by Loughlin (1991). So in order to separate the dolomite from limestone, PCA analysis on 5,6,7,8 ASTER bands was done. The following table (1) shows the eigenvector statistics ,that with considering PCA properties we could find dolomite in PC4 with negative loading (figure b) that indicating that pixels likely to contain dolomite will be represented by low (dark) DN values in PC4. To facilitate visualization, the PC4 image is then negated (by multiplying all pixels by -1), so that the target material is displayed as bright pixels in the respective abundance image. (Figure c) Table (1): Eigenvector statistics for ASTER bands 5, 6, 8 and 7
 Figure (b): PC4 in PCA Analysis that indicating That pixels likely to Contain dolomite will be Represented by Low (Dark) DN values |