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— In this study, we have compared results of three image processing techniques; Spectral indices (SI), Featured Principal component analysis (FPCA) and Band ratio (BR) using ASTER satellite remote sensing data for lithological discrimination at Lakhra, Sindh. SI for minerals like Calcite, Dolomite, Laterite (Iron oxides) and Clay are generated using VNIR & SWIR bands, on basis of spectral absorption features of major rock forming minerals. Principal components are produced using Crosta Technique to decorrelate calcite and -OH (clay) minerals. Eigen values of PC-3 have maximum decorrelation values (0.851484 & - 0.463157 in band 6 & 8) indicating presence of calcite. Also, Eigen vector values of PC-4 (-0.675364 & 0.714621) for band 5 and 6 indicate presence of –OH bearing clay minerals. Band Ratios (4/3-5/8-4/6) are used to discriminate rocks based upon their mineralogical compositions. Overall, Spectral Index method with 64% accuracy, is found to be the most effective technique among the others for lithological mapping of major rock units including carbonate (limestone, dolomite), shale (clays) & laterite (Fe oxide minerals). Comparison of satellite image processing results shows a good agreement with field samples and geological map of study area.

Muhammad Anees, Muaaz Shoukat, M. Akbar Kha, Mussawir Abbasi. (2017) Comparison of Remote Sensing Algorithms for Discrimination of Major Rock Units Using ASTER Data at Lakhra Anticline, Sindh, Pakistan, Journal of Space Technology , Volume 7, Issue 1.
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