Abstract
— 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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