Exploring Porphyry Copper Deposits in the Central Iran Using Remote Sensing Techniques

Abstract

This study used the ability of remote sensing technology to identify alteration zones in porphyry copper mining and Iron oxides of area in south Nain district in Iran by using Lands at-8 data source. The band ratio of 3/2 derived from image spectra was used to indicate the distribution of iron oxides and 6/3 for identifying gossan. Hydrothermal alteration mineral zones associated with porphyry copper mineralization identified and discriminated based on two algorithms of target detection, MTTCIMF and OSP. Those techniques identified porphyry copper mineralization in study area and six points were diagnosed as the best location for ore exploration. For more accurate study and recognition between mineralization and tectonic structure of district, the lineament map of area was produced by applying Gaussian high-pass filter on IRS data. The Spatial distribution of hydrothermal alteration zones has been verified by inspection in field works and Fuzzy logic. Results showed that image processing techniques have a great ability to obtain comprehensive information for reconnaissance stage of porphyry copper exploration in the case study and assist researcher to explore porphyry copper and iron oxides regions before time-consuming and costly ground investigation.