The challenge remains for the mining industry to identify the mechanisms by which to cost effectively forecast and manage geoenvironmental risks at the earliest possible stage in a mine’s life. If adequately performed, appropriate allocation of funds and environmental management strategies can be developed and embedded into the mine plan enabling better closure outcomes. Whilst the metalliferous mining industry is cognisant of this, another major challenge is finding the right tools to facilitate early stage waste characterisation. For example, chemical (i.e., static and kinetic) tests have dominated how AMD properties have been measured since the late 1970s, but with AMD remaining an ongoing global issue (even at young mines), there is a necessity for innovation. With an explosion of new tools and technologies for ore characterisation, there has never been a more opportunistic time to follow an environmental geometallurgy matrix approach whereby the geoenvironmental toolbox is used for waste characterisation. The toolkit includes application of hyperspectral technologies to derive geoenvironmental domaining index and automated acid rock drainage index values, improved used of handheld tools and chemical tests, data mining, and finding new applications for µCT and 3D XRF drill core scanners. This paper focusses on demonstrating applications of hyperspectral datasets as the metalliferous mining industry trend is currently towards collecting these data during early life-of-mine stages. As we approach the next decade, the industry has the unique opportunity to adopt the environmental geometallurgy matrix and embed the use of the geoenvironmental toolbox into their operations to improve risk management
