Per-pixel analysis of ASTER data for porphyry copper hydrothermal alteration mapping: A case study of NE Isfahan, Iran

Abstract

This paper evaluates the efficiency and capability of per-pixel methods comprising spectral feature fitting (SFF), multi range spectral feature fitting (MRSFF), and spectral information divergence (SID) algorithms in mapping alteration minerals using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. The study area is located in the Saveh-Yazd belt, northeastern Isfahan, Iran, which is the central part of the Urumieh–Dokhtar Magmatic Arc (UDMA). Porphyry copper mineralization formed in association with Oligo-Miocene intrusive bodies, are located in this belt. The hydrothermal alteration zones in the study area are manifested by phyllic, argillic, propylitic, and silicic. Mineralogically, these zones are marked by sericite-illite, kaolinite, montmorillonite, chlorite, epidote, and overprint of iron oxide/hydroxides. The pixel purity index (PPI) was used for extraction of image spectra, which were subsequently used as spectral reference. The SFF algorithm could map the Al–OH bearing mineral assemblages as a mixed alteration zone (phyllic-argillic zone), whereas the MRSFF provided an improved discrimination of sericite-illite and kaolinite minerals. The SID algorithm had the best performance for identifying and mapping these alteration minerals, comparing to the SFF and MRSFF. On the other hand, the results showed that SID and MRSFF algorithms were more efficient than SFF in discriminating the propylitic alteration zone. The field surveys, X-ray diffraction, spectral measurements, and microscopic studies confirmed the occurrence of hydrothermally altered minerals containing sericite-illite, kaolinite-dickite, and chlorite– epidote, which corresponded well to the ground criteria. Considering the potential of SID algorithm in discriminating the target minerals, it could be proposed for mineral mapping as part of exploration projects.