HR: 0800h
AN: MR11B-0940    [Abstracts]
TI: Regional Mineral Potential Mapping in the Kangneung, Korea using GIS and Probability Model
AU: * Lee, S
EM: leesaro@kigam.re.kr
AU: Kim, I
AU: Kim, Y
AB: The most common approach to mineral potential mapping is data-driven and exploits knowledge about how known deposits spatially relate to their surroundings. The aim of this process is to analyze relationships between metallic mineral deposits and related factors to identify areas that have not been subjected to the same degree of exploration. This empirical approach assumes that all deposits share a common genesis and comprises three main steps such as identification of spatial relationships, quantification of identified spatial relationships and integration of multiple quantified spatial relationships. For this, a spatial database including metallic mineral deposit, topographic, geologic, geophysical and geochemical data were constructed for Kangwondo area in Korea using GIS. The used 391 mineral deposits were Cu, Pb, Zn, W, Mo and Fe and as the related factors, topographic data such as DEM and slope, geological data such as lithology and fault, geochemical data such as Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Si, Sr, V, Zn, Cl-, F-, PO42-, NO2-, NO3- and SO42--, geophysical data such as freeair, Bouguer and magnetic anomaly were used. Using the constructed spatial database, the relationships between minerals deposit areas and related factors were identified and quantified by probabilistic model. Among the factors, distance from Faults, Ca, Fe, Mg, Ph, SO4 and W were used for mapping of regional mineral potential using overlay method in GIS environment because there were close relationship (R2 > 0.5) between mineral deposit and the factors. Then, the mineral potential map was verified using rate curve method. The verification results showed satisfactory agreement between the mineral potential map and the existing mineral deposit area. A GIS was used to efficiently analyze the vast amount of data, and the probability model was turned out be an effective tool to analyze the mineral potential mapping.
DE: 3665 Mineral occurrences and deposits
SC: Mineral and Rock Physics [MR]
MN: 2004 AGU Fall Meeting