MINERAL IDENTIFICATION BY BAND RATIOS AND FEATURE ORIENTED PRINCIPAL COMPONENT SELECTION TECHNIQUES IN THE BHUKIA REGION, RAJASTHAN

摘要

The applications of remote sensing are dynamic and ever growing. In the field of mineralogy in particular, the application of remote sensing reached a new dimension with the advent of hyperspectral remote sensing which includes both imaging and spectroscopy in a single system. The basic concept behind this mineral identification through remote sensing lies in the minerals' uniqueness in the reflectance and absorption pattern across different wavelengths. In this study Band Rationing and Feature Oriented Principal Component Selection (FPCS) have been applied to VN1R-SWIR bands of ASTER data set to identify the minerals in the study area. By studying the spectral signatures of the minerals in the spectral range of the datasets and by referring to certain previous works, appropriate Band Ratios have been operated and the minerals have been identified and matched through the USGS spectral mineral library. With this basic approach, the FPCS technique has also been applied where Principal Component Analysis (PCA) has been functioned on a set of four bands selected by considering the spectral signatures of the minerals and then analyzing the eigenvectors. Mineral spectra have also been generated from the field samples for the validation purpose and the spectra thus obtained have been matched with the USGS spectral mineral library. Finally, calcium rich minerals such as Dolomite, Diopside, Calcite, and Talc, clay minerals such as Kaolinite, Illite, Montmorillonite and Nontronite and a few iron rich minerals such as Pyrrhotite, Jarosite and Hematite have been documented. The minerals obtained were in support of the GSI geological map of the area.