Mineral Mapping through Advanced Airborne Hyperspectral Remote Sensing Techniques

Abstract

An increased number of spectral channels in the visible to near-infrared region (VNIR) and short-wave infrared region (SWIR) in hyperspectral sensors help in the identification of distinct variations in minerals. Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral sensor with 425 spectral bands is useful for mineral Constrained Energy Minimization (CEM), Spectral Angle Mapper (SAM), and Adaptive Coherence Estimator (ACE) advanced tools utilized to detect target minerals in the study area for mineral exploration. Minimum Noise Fraction (MNF), ACE, SAM and CEM advanced hyperspectral remote sensing techniques were applied to the AVIRIS-NG airborne data to map the kaolinite, dolomite, chlorite and hematite. In the MNF images, some areas are prominently highlighted and identified as areas of interest. CEM algorithm has classified the four minerals better than the ACE and SAM. The potential zones identified from the remote sensing data were verified, and abandoned old mines are present in three locations out of four. These locations are picked up well in different MNF images. In the mapped area, carbonate is present in the form of altered minerals in metabasalt, and iron leached surface indicates hematite mineral. The remote sensing outputs well also supported by the petrographic studies. The approach used in this study has great implications for mineral mapping.