Uncertainty in GIS-based prospectivity mapping in greenfields and undercover terranes

Given the potential for the discovery of significant mineral deposits in greenfields terranes, as well as undercover, the methods used for GIS-based prospectivity mapping must be examined and adapted to address the challenges faced with exploration in these regions. As the quality of a prospectivity map can be dependent on both the understanding of a mineral system as well as the quality and quantity of the input datasets, the issue of how to quantify uncertainties must be addressed. Uncertainties may arise from the mathematical models used, data quality issues, and human bias. While mathematical uncertainties can generally be quantified using different statistical measures, it is more difficult to quantify the uncertainty related to human bias and data quality. Different methods for data interpretation and analysis are investigated to reduce the degree of uncertainty and to measure this value in a quantitative way when undertaking a prospectivity mapping exercise