A remote sensing-based discrimination of high- and low-potential mineralization for porphyry copper deposits; a case study from Dehaj–Sarduiyeh copper belt, SE Iran

This work seeks to implement surface indicators of porphyry copper deposits (PCDs) at known source regions and to apply these indicators to recognize high- and low-potential mineralization through remote sensing in other areas. Thirty copper deposits in central Iranian volcano-sedimentary complex, Kerman province, Southeast of Iran, which are different in grade and size, were selected as test sites. The abundances of alteration minerals at these deposits were discriminated using a partial sub-pixel unmixing algorithm, mixture tuned matched filtering (MTMF), on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to find​ an indicator whether the abundances of alteration minerals correspond to the grade and size of each deposit. In general, comparison of sub-pixel abundances with known mineral occurrences showed a reasonable correspondence such that areas with high abundances of alterations corresponded well with important mineralized districts. It is concluded that suggested sub-pixel analysis of ASTER data leads to identifying alteration zones with high-potential mineralization in PCDs.