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

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Abstract

A case application of data-driven estimation of evidential belief functions (EBFs) is demonstrated to prospectivity mapping in Lundazi district (eastern Zambia). Spatial data used to represent recognition criteria of prospectivity for aquamarine-bearing pegmatites include mapped granites, mapped faults/fractures, mapped 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 evidential map layer and target deposits but also (b) spatial relationships between classes of evidences in an evidential map layer. Data-driven estimates of EBFs can indicate which spatial data provide positive or negative evidence of prospectivity. Data-driven estimates of EBFs of only spatial data providing positive evidence of prospectivity were integrated according to Dempster’s rule of combination. Map of integrated degrees of belief was used to delineate zones of relative degress of prospectivity for aquamarine-bearing pegmatites. The predictive map has at least 85% prediction rate and at least 79% success rate of delineating training and validation deposits, respectively. The results illustrate usefulness of data-driven estimation of EBFs in GIS-based predictive mapping of mineral prospectivity. The results also show usefulness of EBFs in managing uncertainties associated with evidential maps.

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Carranza, E.J.M., Woldai, T. & Chikambwe, E.M. Application of Data-Driven Evidential Belief Functions to Prospectivity Mapping for Aquamarine-Bearing Pegmatites, Lundazi District, Zambia. Nat Resour Res 14, 47–63 (2005). https://doi.org/10.1007/s11053-005-4678-9

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