Abstract
To address the significant challenges posed by varying methodologies across diverse environments, it is imperative to enhance innovative approaches for Mineral Prospectivity Mapping (MPM). A significant issue arises in greenfield regions, where determining the appropriate weights for various geospatial layers in MPM leads to a considerable difficulty. Given the scarcity of known deposits of similar types in these areas, relying on experienced geologists for layer weighting often results in biased outcomes that reflect the subjective views of the experts. This study utilized available geological, airborne geophysical, geochemical, and remote sensing datasets to develop reliable evidence layers for gold exploration, despite the fact that much of the study area is covered by alluvial deposits and has only a few known occurrences of gold and copper. The prediction-area (P-A) method was used to assess the weight of each geospatial layer, independent of the geologist's subjective evaluations. This data-driven approach quantifies the significance of each layer by analyzing the ratio of known deposits to their respective areas. Ultimately, these calculated weights were utilized to create a gold prospectivity map for the region through a modified TODIM and multi-index overlay (MIO) method. The TODIM method, a sophisticated pairwise comparison technique that accommodates preferences for either profit or loss, was refined through subtle adjustments to its calculation algorithm, enhancing its efficiency in managing a multitude of alternatives. In our approach, we employ a classification procedure rather than a ranking system to determine the final outputs of TODIM. To assess the efficacy of the modified TODIM, we utilized the index overlay method as a benchmark for performance evaluation.
Published Version
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