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Analysis and modeling of geospatial datasets for porphyry copper prospectivity mapping in Chahargonbad area, Central Iran

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Abstract

In mineral exploration, proposing new prospects is a main issue and geospatial information system (GIS) offers different techniques for this procedure. Mineral prospectivity maps (MPMs) can reduce costs and errors for predicting mineral potentials. In this research, data layers have been analyzed and integrated for porphyry copper mineral prospectivity mapping in Chahargonbad sheet of Kerman Province, Central Iran. First of all, geological, geochemical, geophysical, and satellite imagery have been processed separately and assigned according to their favorability in porphyry copper mineralization using index overlay and fuzzy logic methods which was lead to introduce two priorities for further exploration. Eight hundred forty-six geochemical stream sediment samples were analyzed using multifractal concentration-number model to generate geochemical anomaly maps. Afterward, airborne magnetic data was used to extract magnetic edges which can represent structures (faults and fractures) and lithological contacts. Airborne radiometric data is also used to identify felsic units based on K, Th, and U (RGB) ternary image. Thereafter, satellite imagery (ASTER, ETM+ images) was processed based on relative absorption band depth (RBD), principle component analysis (PCA) and Crosta methods in order to separate alteration zones in the study area. Totally, 80 km2 has been detected as the first priority that is located in the northwest (Kuh Panj), center (south of Hamid Abad and east of Sorkhgino), southeast (Chenar Kaf), and southwest (north of Alimoradi) of this sheet. Also, the second priority (97 km2) is located in the center (southeast of Syloieh), southeast (Chenar Kaf), east (Cheheltan), and northwest (south of Kuh Panj).

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Yazdi, Z., Jafari Rad, A.R. & Ajayebi, K.S. Analysis and modeling of geospatial datasets for porphyry copper prospectivity mapping in Chahargonbad area, Central Iran. Arab J Geosci 8, 8237–8248 (2015). https://doi.org/10.1007/s12517-014-1740-0

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