ASTER and landsat TM remote sensing data for geological mapping application: case study esfandaghe ophiolite complex south of Iran

Abstract

This study developed an approach to discriminate lithological units using ASTER and Landsat TM satellite data at a regional scale. Spectral transform approaches, including Principal Component Analysis (PCA) and Band Ratioing (BR) were applied to distinguish rock units and the identification of high-potential areas of chromite ore deposits within ophiolite complex. In order to determine the best RGB color composite in the satellite images, Correlation Coefficient and Optimum Index Factor (OIF) methods were utilized. Soghan ophiolite complex located in SE Iran has been selected as the case study for applying the image processing techniques. The results indicated that the methods used evidently showed superior outputs to study ophiolitic complex rock units. The new band ratio (4/1, 4/5, 4/7) and PCA (1, 2, 3) on ASTER and PCA (1, 3, 4) on Landsat TM satellite data were used to discriminate ophiolitic rock units. Furthermore, the results showed that the correlation coefficient and optimum index factor (OIF) methods can efficiently determine the best RGB color band combination using ASTER and Landsat TM data for lithological mapping. Consequently, RGB images (7, 5, 1) and (5, 4, 1) of Landsat TM and RGB (7, 4, 1) and (7, 2, 1) of ASTER were selected to accomplish better color composites for visual interpretation of the Soghan ophiolite complex. The developed approach offers great potential for mapping host rocks of chromite ore deposit within vast ophiolite complexes, which contribute significantly to geological economics by identifying new chromite prospects.