Application of Data-Driven Evidential Belief Functions to Prospectivity Mapping for Aquamarine-Bearing Pegmatites, Lundazi District, Zambia

摘要: A case application of data-driven estimation evidential belief functions (EBFs) is demonstrated to prospectivity mapping in Lundazi district (eastern Zambia). Spatial data used represent recognition criteria for aquamarine-bearing pegmatites include mapped granites, faults/fractures, shear zones, and radioelement concentration ratios derived from gridded airborne radiometric data. Data-driven estimates EBFs take into account not only (a) spatial association between an map layer target deposits but also (b) relationships classes evidences layer. can indicate which provide positive or negative evidence prospectivity. providing were integrated according Dempster’s rule combination. Map degrees was delineate zones relative degress pegmatites. The predictive has at least 85% prediction rate 79% success delineating training validation deposits, respectively. results illustrate usefulness GIS-based mineral show managing uncertainties associated with maps.