Abstract
Reflectance spectroscopy allows cost-effective and rapid mineral characterisation, addressing mineral exploration and mining challenges. Shortwave (SWIR), mid (MIR) and thermal (TIR) infrared reflectance spectra are collected in a wide range of environments and scales, with instrumentation ranging from spaceborne, airborne, field and drill core sensors to IR microscopy. However, interpretation of reflectance spectra is, due to the abundance of potential vibrational modes in mineral assemblages, non-trivial and requires a thorough understanding of the potential factors contributing to the reflectance spectra. In order to close the gap between understanding mineral-diagnostic absorption features and efficient interpretation of reflectance spectra, an up-to-date overview of major vibrational modes of rock-forming minerals in the SWIR, MIR and TIR is provided. A series of scripts are proposed that allow the extraction of the relative intensity or wavelength position of single absorption and other mineral-diagnostic features. Binary discrimination diagrams can assist in rapidly evaluating mineral assemblages, and relative abundance and chemical composition of key vector minerals, in hydrothermal ore deposits. The aim of this contribution is to make geologically relevant information more easily extractable from reflectance spectra, enabling the mineral resources and geoscience communities to realise the full potential of hyperspectral sensing technologies.
Highlights
Minerals produce diagnostic features across the visible and infrared part of the electromagnetic spectrum
Asymmetry of absorption features The are useful parameters can be extracted from hyperspectral reflectance spectra features are useful parameters that can be extracted from hyperspectral reflectance spectra and these have been traditionally used for estimating relative mineral abundance, trackthesechemistry have beenand traditionally used for estimating relative mineral abundance, ing and mineral determining crystallinity, amongst other applications
Integration of the VNIR-SWIR reflectance spectroscopy-based map of transported sediments, with drill core mineralogy, into one seamless 3D mineral model helped to improve (1) the determination of the channel–basement contact by means of an absorption-feature-based kaolin crystallinity index, (2) the delineation of the resource by adding continuous ironoxide abundance data at the surface to sparse data points at depth collected along the drill strings, and (3) the characterisation of channel iron ore and potential penalty minerals by better mapping the mineralogical zones within the ore body, such as clay horizons interlayered with high-grade channel iron ore horizons
Summary
Minerals produce diagnostic features across the visible and infrared part of the electromagnetic spectrum. Reflectance spectra measured from geological materials such as rocks and soils contain spectral signatures or “fingerprints” of their constituent minerals and other components and properties, from which can be derived information including mineral species, abundance, chemistry and crystallinity As this contribution aims to summarise the absorption features of minerals independent of instrument specifications, the respective vibrational modes are described in the following wavelength ranges (Figure 1): (i) SWIR 1 = 1300 to 1850 nm, (ii) SWIR 2 = 1850 to 2600 nm, (iii) MIR = 2600 to 5500 nm and (iv) TIR = 5500 to 15,000 nm. Many other challenges, such as surface contaminants (e.g., sulphate crusts forming on stored drill core material), moisture content in sample material and measurement environment, as well as contaminated calibration panels, further complicate the interpretation of reflectance spectra.
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