Near-infrared (NIR) and short-wavelength infrared (SWIR) hyperspectral imagery can be used to detect certain alteration minerals. At epithermal deposits, the formation of alteration minerals is, in theory, related to the mineralisation of gold and silver. In order to provide foundations for developing sensor-based sorting applications at a mine that exploits such a deposit, it was investigated if NIR-SWIR hyperspectral imagery can be used to distinguish between ore and waste particles by characterising the alteration mineralogy. Maps were produced from the NIR-SWIR hyperspectral images of 827 drill core samples that show mineral occurrences, mineral absorption feature intensities and characteristics of the iron oxide mineralogy. Partial least squares discriminant analysis (PLS-DA) was applied to the information contained in these maps to investigate if this information can be used to discriminate between ore and waste. The results showed that NIR-SWIR hyperspectral imagery could be used to segment a population of waste samples by detecting occurrences of pyrophyllite, dickite and/or illite. This result can be explained by the fact that these minerals are commonly deposited further away from the ore-bearing epithermal veins, while the absence of SWIR-active minerals or detected occurrences of alunite are more closely associated with these structures. The ability to identify waste with NIR-SWIR spectral sensors means there is potential that sensor-based sorting can be used to remove this waste from mineral processing operations. Additional research is still required to assess the economic feasibility of such a sensor-based sorting application.

A recent study by Dalm et al. (2014) showed that alteration mineralogy acquired using SWIR point spectrometry could be linked to copper grade distribution for a group of samples from a South American copper mine. Since it was expected that SWIR hyperspectral imagery can provide more detailed information about the alteration mineralogy of these ores, we investigated whether this technique can be used to improve upon the indirect characterization of copper grades. Maps showing the distributions of SWIR-active minerals, white mica crystallinity, white mica composition, and chlorite composition were produced from SWIR hyperspectral images of 43 samples from the Dalm et al. (2014) study. Subsequently, a principle component analysis (PCA) was applied to the relative mineral abundances and the average white mica crystallinity and composition that were extracted from these maps. The PCA showed that this mineralogical data could be used to discriminate a significant portion of the samples with sub-economic copper grades. Furthermore, the study showed that SWIR hyperspectral imaging has the following advantages over SWIR point spectrometry: minerals that are present in relatively low quantities can be detected, the SWIR-active mineralogical composition at the surface of a sample can be quantified, and the texture of samples, such as grain sizes and cross-cutting vein structures, can be characterized. However, these advantages did not improve upon the indirect characterization of copper grades that was achieved using SWIR point spectrometry. This was attributed to the relatively small size of the sample set and the high textural variability between samples.

This paper shows the results of Short-Wavelength Infrared (SWIR) spectroscopy investigations of volcanic rocks sampled from low-grade metamorphic greenstone belts of the Archean Pilbara Craton in Western Australia. From the reflectance spectra a range of spectrally active minerals were identified, including chlorites, hornblende, actinolite, epidote and white micas. The rock samples were grouped into mineral assemblages based on their spectrally identified minerals and stratigraphic positions. The metamorphic amphibolite and greenschist facies could be identified from the SWIR spectroscopic data as well as three sub zones of the greenschist facies: 1) a zone containing Fe-chlorite; 2) a zone containing intermediate chlorite and epidote; and 3) a zone containing intermediate chlorite, actinolite and hornblende. Spectral parameters were calculated from the reflectance spectra to assess the metamorphic grade and zones. Plots of the depth parameters of the Fe-OH feature near 2250 nm versus the Mg-OH feature near 2390 nm differentiate the metamorphic amphibolite and greenschist facies and a transition zone between the two. The wavelength position parameter of the Mg-OH absorption feature near 2340 nm also serves to discriminate between the various metamorphic sub zones.The identification of the metamorphic grades of the volcanic sequences in greenstone belts with SWIR spectroscopy is useful for regional geological field studies, exploration for metamorphic mineral deposits hosted in the greenstone belts and the interpretation of hyperspectral remote sensing data sets covering similar types of terranes.