Regional Probabilistic and Statistical Mineral Potential Mapping of Gold–Silver Deposits Using GIS in the Gangreung Area, Korea |
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| Authors: | Hyun-Joo Oh Saro Lee |
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| Institution: | Department of Earth System Sciences, Yonsei University, Seodamun-Gu, Seoul, Korea;, Geoscience Information Center, Korea Institute of Geoscience and Mineral Resources (KIGAM), Yusung-gu, Daejon, Korea |
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| Abstract: | The aim of the present study is to analyze relationships between epithermal Au‐Ag deposits of the hydrothermal type and related geological factors and integrate the relationships using probabilistic and statistical models in a geographic information system (GIS) environment. A variety of spatial geological data were compiled, evaluated and integrated to produce a map of potential Au and Ag deposits in the Gangreung area, Korea. This empirical approach assumes that all deposits shared a common genesis. The method consists of three main steps: (i) identification of spatial relationships; (ii) quantification of such relationships and (iii) integration of multiple quantified relationships. A spatial database containing Au and Ag deposits, topographic, geologic, geophysical and geochemical data was constructed using a GIS. The factors relating to 103 Au and Ag mineral deposits are the geological data such as lithology and fault structure, geochemical data including the abundance of Al, As, Ba, Ca, Cd, Co, conductivity, Cr, Cu, Eh, Fe, HCO3–, K, Li, Mg, Mn, Mo, Na, Ni, Pb, pH, Si, Sr, V, W, Zn, Cl?, F?, PO43?, NO2?, NO3? and SO42?, and geophysical data including Bouguer and magnetic anomalies. Using the constructed spatial database, the relationships between mineral deposit areas and 36 related factors are identified and quantified by probabilistic and statistical modeling; that is, likelihood ratio, weights of evidence and logistic regression. All the factors were combined to produce a map of the regional mineral potential using the overlay method in a GIS environment. The mineral potential map was then verified by comparison with known mineral deposits. The verification results give respective accuracies of 82.52%, 72.45% and 81.60% for the likelihood ratio, weights of evidence and logistic regression models, respectively. The mineral potential map can be used as a source of basic information for mineral resource development. |
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| Keywords: | Au-Ag GIS Korea likelihood ratio logistic regression mineral potential mapping weights of evidence |
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