Lithological mapping is a fundamental step in various mineral prospecting studies because it forms the basis of the interpretation and validation of retrieved results. Therefore, this study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti Atlas. This task was completed by using principal component analysis (PCA), band ratios (BR), and support vector machine (SVM) classification. Overall accuracy and the kappa coefficient of SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination.
Lithological mapping is one of the fundamental steps in the various mineral prospecting studies, because it forms the basis of the interpretation and validation of retrieved results. Therefore, this study exploited the multispectral ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 8 data in order to map lithological units in the Bas Drâa inlier, at the Moroccan Anti atlas. This task was completed by using the principal component analysis (PCA), band ratios (BR) and support vector machine (SVM) classification. Overall accuracy and the kappa coefficient of SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological maps and previous works on the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 data in lithological units discrimination.
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