An AHP–TOPSIS predictive model for district-scale mapping of porphyry Cu–Au potential: a case study from Salafchegan Area (Central Iran)

The Salafchegan area in central Iran is a greenfield region of high porphyry Cu–Au potential, for which a sound prospectivity model is required to guide mineral exploration. Satellite imagery, geological geochemical, geophysical, and mineral occurrence datasets of the area were used to run an innovative integration model for porphyry Cu–Au exploration. Five favorable multi-class evidence maps, representing diagnostic porphyry Cu–Au recognition criteria (intermediate igneous intrusive and sub-volcanic host rocks, structural controls, hydrothermal alterations, stream sediment Cu anomalies, magnetic signatures), were combined using analytic hierarchy process and technique for order preference by similarity to ideal solution to calculate a final map of porphyry Cu–Au potential in the Salafchegan area

Hyperspectral scanning of precipice outcrop. Final Report ANLEC Project 7-0115-0237

This report brings together disparate disciplines\ua0 to investigate automated (machine learning) analysis of hyperspectral, Xray and photogrammetric scanner data for identification of lithologies, in particular coal quality, for the prediction of coal lithotypes, breakage behaviour and washability. It was a joint project between the UQ JKMRC\ua0 and School of Earth and Environmental Sciences, and the commercial company CoreScan, and DNRM's Hylogger capability. The report can be obtained from www.acarp.com.au