Comparison of ASTER and ETM+ data for exploration of porphyry copper mineralization: A case study of Sar Cheshmeh areas, Kerman, Iran Geology of the area The volcanic-sedimentary rocks of Eocene age are the oldest rocks in the Sar Cheshmeh area represented by pyroclastics, pyroxene trachyandesites, pyroxene andesites, trachyandesites, trachybasalts and andesites. The sedimentary rocks in the volcanic-sedimentary complex are mainly sandstone and less frequently limestone that has subordinate development in the area. The Eocene volcanic sedimentary rocks are intruded by Oligocene-Miocene plutonic rocks that consist of mainly granodiorite, quartz-diorite, diorite, monzonite, tonalite and granite. The volcanic rock in the immediate vicinity of these intrusives are widely metamorphosed and altered. Most of the plutonic and volcanic rocks are hydrothermally altered and at places they are mineralized. Argillization, sericitization and propylitization are the most common types of hydrothermal alteration in the area. The Neogene sediments consist of mainly loosely consolidated, unsorted and poorly stratified conglomerate and sandstone overlying the Eocene volcanic-sedimentary rocks. Calcarious terraces, dacitic rocks and recent alluvium are the main Quaternary features in the area. Data analysis The principal component transformation is a multivariate statistical technique that selects uncorrelated linear combinations (eigenvector loadings) of variables in such a way that each successively extracted linear combination, or principal component(PC), has a smaller variance. The principal component analysis is widely used for alteration mapping in metallogenic provinces. Crosta technique is also known as feature oriented principal components selection. Through the analysis of the eigenvector values it allows identification of the principal components that contain spectra information about specific minerals, as well as the contribution of each of the original bands to the components in relation with spectral response of the materials of interest. This technique indicates whether the materials are represented bright or dark pixels in the principal components according with the magnitude and sign of the eigenvectors loadings. This technique can be applied on ETM+ and ASTER data.  Figure 2: Left image shows the Landsat image prepared by using the eigenvector loadings of PC4. Right image shows the ASTER image prepared by using eigenvector loadings of PC2. In both images bright pixels are the altered areas.
Principal component analysis is done using six ETM+ bands as input Bands (Table 1). The first principal component does not contain spectral features relevant in this analysis, as it is a combination of all Bands. This component contains 91.2 per cent of the variance of six bands. This PC gives information mainly on albedo and topography. Vegetation is enhanced in PC3 as this PC has higher loading of Band-4 (0.84). PC4 enhances the hydroxyl minerals. This PC has higher loadings of Bands 5 (0.51) and 7 (-0.51) but with opposite signs. Hydroxyl image that is prepared by using eigenvector loadings of PC4 is shown in Figure 2. A similar analysis of PC5 shows that the most important contributions come from TM1(-0.43) and TM3(0.64). According to spectral characteristics of iron oxide, it follows that iron oxide will be mapped by bright pixels. Iron oxide image is obtained by using eigenvector loadings of PC5. Similar analysis is done on ASTER data. The first PC shows the albedo. PC2 enhances the hydroxyl bearing areas as this PC has higher loadings of bands 5 and 7 with plus sign and band 9 with negative sign. As band 9 shows absorption over altered areas , this PC can enhance the altered areas.
ETM+ and ASTER data has been analyzed for enhancing the areas with hydrothermal alteration through principal component analysis and Crosta technique. For each data sets hydroxyl image is prepared(Figure 2). The comparison of these images for ASTER and ETM+ data on this study area showed that ASTER data has better capability for recognition of hydrothermal alteration. |