Abstract
This study used the weight of evidence model to delineate prospective areas for gold deposits in the Lupa Goldfield. The method establishes a spatial relationship between known mineral deposits and evidential maps to create a mineral prospectivity map. Four evidential maps derived from geochemical, geological, geophysical, and topographical Digital Elevation Model (DEM) datasets were analysed and integrated to create a mineral prospectivity map. Results have revealed five classes ranked from the highest, high, medium, low, and lowest favourability patterns with probability values of 0.051, 0.0426, 0.0225, 0.0172, and 0.0091, respectively. The highest favourable areas have the best gold potentials based on the presence of predictor patterns from all four evidential maps. The posterior probability map revealed good prediction, existing gold deposits, such as Saza Mine and Shanta Gold Mine, were mapped. Results have shown that the weight of evidence model was successful and can be applied in mineral exploration targeting.
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