Sub-pixel Mapping of Alteration Minerals Using the PRISMA Hyperspectral Data; A Case Study of Daralu Porphyry Copper Deposit, SE Iran

Abstract

ASI (Italian Space Agency) launched the applicative hyperspectral mission, PRISMA (PRecursore IperSpettrale della Missione Applicativa), in March 2019 for Earth Observation. This sensor records 239 spectral bands in VNIR-SWIR regions across the 400–2500 nm range and 30-m spatial resolution and can advance remote-sensing studies for vast applications worldwide. This present research is focused on evaluating the feasibility of the L2D data sets of this satellite for mapping the alteration minerals of a porphyry copper setting, SE Iran, which is critical for exploration projects. The Daralu area is found to be associated with other porphyries such as Sarcheshmeh and Meiduk in the Urmieh-Dokhtar Magmatic Arc (UDMA) a well-known Cu-bearing region, where a wide range of world-class porphyry copper systems have been reported and studied. Based on the studies and software-based analysis of diagnostic absorption features of measured spectra, the alteration minerals mainly consist of goethite, biotite, muscovite, kaolinite, and chlorite. The Mixture Tuned Matched Filtering algorithm (MTMF) was examined for sub-pixel mapping of the desired alteration minerals. Results of this article revealed that performing this algorithm on the PRISMA dataset because of its high SNR, high spectral resolution, and high radiometric resolution was successful in sub-pixel fraction estimates of biotite, chlorite, and goethite minerals as well as SWIR spectrally similar minerals such as muscovite and kaolinite. The fraction map accuracy was verified through X-ray diffraction analysis of surficial samples. Despite the mixed-signal drawback for 30 m spatial resolution of the PRISMA and certain incompatibilities with XRD results, the output maps corresponded well with the ground criteria, so that was concluded the performance of PRISMA L2D data in mapping the alteration minerals is in line with expectations.