TY - JOUR ID - 57891 TI - Mineral Potential Mapping of Copper Minerals Using Geographical Information System (GIS) JO - Scientific Quarterly Journal of Geosciences JA - GSJ LA - en SN - 1023-7429 AU - Karimi, M. AU - Valadan Zoej, M.J. AU - Ebadi, H. AU - Saheb Zamani, N. AD - Faculty of Geodesy & Geomatics Engineering, K. N. Toosi University of Technology (KNTU), Tehran, Iran. AD - National Iranian Copper Industries Company Y1 - 2008 PY - 2008 VL - 17 IS - 68 SP - 170 EP - 181 KW - GIS KW - Mineral potenial mapping KW - Factor map KW - Inference networks KW - Copper deposits DO - 10.22071/gsj.2009.57891 N2 -      Considering the vast area of Iran and extent of her potential mineral reserves (existence of volcanic belt of Urumieh-Dokhtar), a systematic view for mineral deposit exploration and  mineral potential mapping is essential. Lack of a systematic view and appropriate models for collecting, managing and integrating various geo-spatial data from different sources based on various formats make it  difficult to identify, evaluate and proioritize mineral potentials. Since most of the data related to mineral deposit exploration activities are geo-spatial, Geographical Information System (GIS) can describe and analyze interactions, make predictions with models, and provide support for decision-makers. Mineral potential mappig composes of different steps including: identifying mineralization recognition criteria, data perparation and structuring, producing factor maps and integrating factor maps in the appropriate inference networks. In this research conventional models for integrating factor maps have been investigated. Index overlay and fuzzy logic models are selected to be appropriate models for mineral deposit exploration in semi-detailed (regional study) and detailed stages. An integrated model was also proposed based on Boolean, index overlay and fuzzy logic models . For experimental test, the mineral potential map of Rigan Bam copper deposit with appropriate methods in different inference networks have been produced and 3 appropriate inference networks (one network by Fuzzy Logic model and two networks by integrated models) were selected. Results of three selected networks are in a good accordance with drilling results (%75). Proposed model in Rigan Bam copper deposit capability with required variation can be used for other mineral potential areas and site selection of drilling wells. UR - http://www.gsjournal.ir/article_57891.html L1 - http://www.gsjournal.ir/article_57891_054d147ac7dfded3a0f27673a0c0e685.pdf ER -