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Application of Crosta technique for porphyry copper alteration mapping, using ETM+ data: A case study of Meiduk and SAR Cheshmeh areas, Kerman, Iran
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(Singh and Harison, 1985). The principal component analysis is widely used for alteration mapping in metallogenic provinces(Abrams, et al., 1983; Kaufman, 1988; Loughlin, 1991; Bennett, et al., 1993; Tangestani and Moore, 2001).
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 four and six selected bands of TM data( Crosta and Moore, 1989; Rutz-Armenta and Prol-Ledesma, 1998).
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 very 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 (Dimitrijevic et al. (1971).
Meiduk area has almost a similar geology. The Eocene Volcanic-Sedimentary rocks are subdivided into trachybasalt and trachyandesitic tuff, lava flows and porphyrites; tuffs, trachyandesitic and trachybasaltic rocks, tuffaceous sediments, andesitic and basaltic rocks. The intrusive rocks are granodiorite to tonalite. The upper Cretaceous Flysch is the oldest and the Quaternary alluvial deposits and gravel fans are the youngest exposures. Sedimentary rocks consist of the Pliocene and Eocene sandstones, marls, sandy calcarenites and conglomerates(Dimitrijevic, 1973).
Data analysis and discussion
ETM+ data of Sar Cheshmeh (Acquisition date 23/6/2001) and Meiduk ( Acquisition date 11/4/2001) areas are used for this study. Both images are cloud free. The images are geometrically corrected by using control points from topographic sheets. Both subscenes are joined together to form a single image. The general statistics and principal component eigenvectors and eigenvalues are calculated (Table 1).
Table 1: A) General statistics for Meiduk and Sar Cheshmeh areas
| Minimum |
41.000 |
28.000 |
21.000 |
11.000 |
8.000 |
7.000 |
| Maximum |
185.000 |
182.000 |
220.000 |
168.000 |
248.000 |
255.000 |
| Mean |
77.990 |
75.411 |
94.500 |
74.532 |
80.403 |
72.550 |
| Median |
77.000 |
73.000 |
92.000 |
73.000 |
76.000 |
69.000 |
| Std. Dev. |
8.887 |
11.044 |
15.905 |
12.925 |
19.404 |
17.150 |
| Std. Dev. (n-1) |
8.887 |
11.044 |
15.905 |
12.925 |
19.404 |
17.150 |
| Covariance Eigenvalue |
1178.654 |
80.268 |
20.146 |
6.316 |
4.698 |
1.523 |
| Percentage of variance |
91.2 |
6.2 |
1.6 |
0.46 |
0.36 |
0.12 |
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