ExploreSA02 Mar - 31 Jul
The Gawler Challenge
This competition has finished.
Application of a Machine-Learning technique to delineate new targets based on Uranium anomalies
Through this innovative technique, we pinned several targets based on the positive Uranium anomalies output from the machine-learning algorithm employed. This methodology applies the Random Forest regression to integrate multidimensional airborne radiometric data concerning to predict the uranium content generated by environmental effects such as lithology and pedogenesis. Therefore, it is possible to isolate uranium concentration from secondary effects such as weathering, soil alteration, hydrothermal alteration, or mineralization process.