This research was performed with the objective of evaluating the accuracy of spectral angle mapper (SAM) classification using different reference spectra. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital images were applied in the SAM classification in order to map the distribution of hydrothermally altered rocks in the Kerman Cenozoic magmatic arc (KCMA), Iran. The study area comprises main porphyry copper deposits such as Meiduk and Chahfiroozeh. Collecting reference spectra was considered after pre-processing of ASTER VNIR/SWIR images. Three types of reference spectra including image, USGS library, and field samples spectra were used in the SAM algorithm. Ground truthing and laboratory studies including thin section studies, XRD analysis, and VNIR-SWIR reflectance spectroscopy were utilized to verify the results. The accuracy of SAM classification was numerically calculated using a confusion matrix. The best accuracy of 74.01% and a kappa coefficient of 0.65 were achieved using the SAM method using field samples spectra as the reference. The SAM results were also validated with the mixture tuned matched filtering (MTMF) method. Field investigations showed that more than 90% of the known copper mineralization occurred within the enhanced alteration areas.