Abstract The use of satellite images for mineral exploration has been very successful in pointing out the presence of minerals such as smectite and kaolinite which are important in the identification of hydrothermal alterations. Shortwave infrared (SWIR) bands from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the wavelength ofASTERSWIRbands between 1.65 and 2.43 lmhas a good potential for mapping a hydrothermal alteration minerals such as alunite, pyrophyllite, kaolinite, illite–muscovite–sericite, and carbonate. In this range, hydroxide minerals which have been produced by hydrothermal alteration exhibit good absorption compared to shorter or longer wavelengths. In this research which aims to remove atmospheric and topographic effects from ASTER SWIR data, the authors used the log-residual method (LRM) with the minimum noise fraction (MNF) transformation to create a pixel purity index (PPI) which was used to extract the most spectrally pure pixels from multispectral images. Spectral analyses of the clay mineralogy of the study area (east Zanjan, in northern Iran) were obtained by matching the unknown spectra of the purest pixels to the U.S. Geological Survey (USGS) mineral library. Three methods, spectral feature fitting (SFF), spectral angle mapping (SAM), and binary encoding (BE) were used to generate a score between 0 and 1, where a value of 1 indicates a perfect match showing the exact mineral type. In this way, it was possible to identify certain mineral classes, including chlorite, carbonate, calcite–dolomite–magnesite, kaolinite–smectite, alunite, and illite. In this research, two main propylitic and phyllic–argillic zones could be separated using their compositions of these minerals. These two alteration zones are important for porphyry copper deposits and gold mineralization in this part of Iran.
