Advancement of airborne hyperspectral remote sensing techniques provides subtle variations to identify minerals and to make distinctions between rock formations. These techniques clearly define barren land versus economically viable zones containing ores and minerals. As we know profitable mineral zones are commonly associated with hydrothermal alteration zones, hyperspectral remote sensing techniques have the capability to identify and distinguish between altered, weathered, and clay minerals. In this research work, airborne hyperspectral remote sensing image from AVIRIS-NG is used to identify hydrothermally altered minerals in the Jahajpur region of Bhilwara district, Rajasthan, India. The purpose of this study is the identification of the minerals through spectral features of image spectra in corroboration with field sample spectra and USGS laboratory spectra. The spectral angle mapper (SAM) and Spectral Feature Fitting (SFF) algorithms were used for the mapping of the minerals. This study was conducted to prove the capability of AVIRIS-NG hyperspectral remote sensing data to identify zones of profitable mineral deposits.