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There are two major types of iron ore deposits in the Pilbara Province of Western Australia—banded iron formation (BIF)-hosted iron ore deposits and bedded iron deposits (BID), respectively, named martite–goethite and martite–microplaty hematite and the channel iron deposits (CID). These deposits consist mainly of iron oxides such as magnetite, hematite and goethite; the latter have been subdivided into vitreous and ochreous goethite. Combining spectral scanning of diamond drill core, drill chips and pulps collected from these deposits provides a rapid and relatively inexpensive means of assessing the potential mineral makeup within a deposit to make informed qualitative decisions. Additionally, the full width half maximum (FWHM) of the 900 nm 6A1→4T1 crystal field absorption feature within the goethite-dominated region is shown to be related to the type of goethite, namely ochreous and vitreous. The assessment capabilities of the combined metrics are presented in a visual format named as the iron boomerang because of its distinctive manifold. This provides the identification of at least two spectral endmembers comprised of hematite and vitreous goethite, the identification of samples that are moving from a pure hematite to mixed hematite/goethite and lastly into a goethite-dominant-driven regime. [ABSTRACT FROM AUTHOR]

Whole rock geochemical analysis of drill core is crucial for rock classification and understanding the evolution of a geological province. This becomes even more important when access to fresh rock samples is hindered by considerable overburden, such as in the case of the basement to the Eucla Basin sediments in Australia. A partial least squares (PLS) regression method was trialled to model geochemical indices, commonly applied for classification of igneous rocks, from hyperspectral visible-near infrared (VNIR; 350 to 1200 nm), shortwave infrared (SWIR; 1200 to 2500 nm) and thermal infrared (TIR; 6000 to 14,500 nm) reflectance spectra of three drill cores intersecting the basement of the Eucla Basin. Modelling of the Mg# (Mg/Mg + Fe) achieved a high correlation between the calculated and predicted values (i.e. R2 > 0.9) at an RMSE of about 10 %. The 2200 to 2400 nm wavelength region of the SWIR was key in modelling the Mg#, with amphibole and chlorite-related absorption features overlapping with the most important input bands in the PLS model. Modelling of the silicon, calcium, iron, magnesium index (SCFM; SiO 2 /(SiO 2 + CaO + FeO + MgO)) required the TIR wavelength range, where diagnostic spectral signatures of silicates are located. PLS-based modelling of the SCFM achieved even a high correlation (i.e. R2 > 0.8) when the model was developed for one drill core but applied to another drill core that intersects the same lithologies. The third geochemical index trialled was the aluminium saturation index (ASI; Al 2 O 3 /(Na 2 O + K 2 O + CaO), producing high correlation between calculated and predicted ASI when using either, the VNIR-SWIR and the TIR wavelength ranges as input. Our study demonstrates how PLS regression can utilise hyperspectral data to determine geochemical indices, without the cost of full geochemical analysis of every sample in a wide array of rock types. The higher spatial resolution of the modelled geochemistry and the extrapolation of the modelling results to intervals that haven't been sampled for geochemistry supports stratigraphic correlation between drill cores. Furthermore, the combined analysis of geochemical and hyperspectrally-derived mineralogy helps mapping the intensity of weathering of basement as well as mineralogical and physicochemical gradients potentially related to hydrothermal systems. • PLS-based modelling of geochemical indices from hyperspectral reflectance spectra • Correlations between calculated and modelled Mg#, SCFM and ASI are significant. • RMSE of modelled geochemical index values about 10 % on average • Comparison of input bands with reflectance spectra reveals causative relationships. • Modelling results can be used for stratigraphic correlations between drill cores. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract The minerals exploration undercover relies on the understanding of the ore-forming processes and the associated alteration characteristics that are used in vectoring towards a deposit. Previously, the proposed process for forming the 1590 Ma Abra base-metal deposit, hosted at 250 m depth in the Paleoproterozoic Edmund Basin of the Western Australian Capricorn Orogen, was through exhalation to the seafloor (SEDEX-style). Lacking any visible signs of alteration, sediments overlying the Abra deposit were perceived as younger, unaltered, and cutting the mineralisation and associated alteration comprised of siderite, chlorite and minor sericite. However, a recent study delineated a phengitic (i.e. Al-poor, Mg-, Fe-, Si-rich) white mica footprint in regolith above the deposit from hyperspectral field and remote sensing data. This study links the surficial mineral footprint to the deposit below through detailed analysis of hyperspectral data from drill core. The hyperspectral data processing results were validated using optical microscopy, micro-XRF and SEM-EDS analysis, and compared with geochemical, lithological and structural drill core data. Hyperspectral short-wave infrared (SWIR) data revealed a vertically zoned alteration footprint from the deposit to the surface, where very fine-crystalline phengitic white mica (i.e. sericite) and chlorite are most abundant a few tens of metres above the deposit. The abundance of chlorite gradually decreases, and the distal phengitic alteration is cut by the present erosional surface, but only moderately affected by weathering, confirming the surficial footprint detected in the previous study. Similarly, a vertically zoned carbonate alteration was delineated from thermal infrared (TIR) reflectance spectra from drill cores up to 2 km away from the deposit. Carbonate alteration from proximal to distal comprised of Mn-rich siderite, ankerite and ferroan dolomite, which replace the dolomite matrix in coarse-grained stratigraphic sequences. The replacement of dolomite matrix suggests that these permeable horizons acted as fluid conduits, which channelled hydrothermal fluids into sedimentary strata from a feeder structure. The presence of a vertically zoned carbonate and chlorite-phengite footprint in the overlying sediments advocates for their deposition before the ore formation at Abra, and a sub-seafloor replacement within a permeable sedimentary sequence as the ore-forming process. Comparable alteration footprints have been described around some world-class sediment-hosted base-metal deposits, including the Sullivan in the British Columbia, which is considered as a classic SEDEX-style by some and an exhalative-replacement hybrid by others. Also, identical footprints are common around the volcanic-hosted massive sulphide and are associated with the carbonate replacement-style deposits – an overlap which is an interesting future research space where hyperspectral technologies could provide answers. Validated hyperspectral data combined with geochemical, lithological and structural information enabled the identification of a subtle mineral footprint above the Abra deposit, and the established method can be used for vectoring towards other buried mineralisations – even through weathering. [ABSTRACT FROM AUTHOR]

Accurate maps of Earth’s geology, especially its regolith, are required for managing the sustainable exploration and development of mineral resources. This paper shows how airborne imaging hyperspectral data collected over weathered peridotite rocks in vegetated, mountainous terrane in New Caledonia were processed using a combination of methods to generate a regolith-geology map that could be used for more efficiently targeting Ni exploration. The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM). This rationale being the spectral features extraction can rapidly reduce data complexity by both targeting only the diagnostic mineral absorptions and masking those pixels complicated by vegetation, cloud and deep shade. SVM is a supervised classification method able to generate an optimal non-linear classifier with these features that generalises well even with limited training data. Key minerals targeted are serpentine, which is considered as an indicator for hydrolysed peridotitic rock, and iron oxy-hydroxides (hematite and goethite), which are considered as diagnostic of laterite development. The final classified regolith map was assessed against interpreted regolith field sites, which yielded approximately 70% similarity for all unit types, as well as against a regolith-geology map interpreted using traditional datasets (not hyperspectral imagery). Importantly, the hyperspectral derived mineral map provided much greater detail enabling a more precise understanding of the regolith-geological architecture where there are exposed soils and rocks. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is a powerful tool for mineral mapping and increasingly used in poorly-accessible areas. It only requires a limited amount of validation sample points, but can fail to discriminate spectrally-similar features. In this manuscript, we show that we improve the identification of interesting targets by including geomorphological data in the spectral mapping scheme. We jointly use geomorphic and spectral features to locate gossanous ironstone ridges as an indicator for possible Pb-Zn-Ag-mineralization and provide an application around Mount Isa and George Fisher/Hilton mine, Queensland, Australia. We combine hyperspectral HyMap data using mixture tuned matched filtering with topographical indices, such as maximum curvature and the topographical position index. As it is often the case with structurally-controlled mineralization, the amount of training sites is limited, and supervised classification methods cannot be implemented. Therefore, we implement expert knowledge in a decision tree to take advantage of the relationship between mineralization, alteration and structure. Optimized rock sampling and spectral measurements provided data for validation. We are able to map sets of gossanous ridges with a minimum of validation points, not only within the Mount Isa mining area itself, but also outside the commonly-accepted host rocks. The ridges are parallel to north-south trending geomorphological features and probably associated with the Paroo fault zone. Similarities between the ridges were confirmed by field observations, spectral measurements and a qualitative rock sample analysis. We identified new mineralized ridges that we could subsequently attribute to a poorly-known and sub-economic deposit known as the Mount Novit Pb-Zn-deposit. [ABSTRACT FROM AUTHOR]

Abstract: A simple quadratic method is proposed for estimating the wavelengths of absorption features in the short wave infrared spectral region from hyperspectral instruments ranging from 2 to 18nm sampling intervals. The method uses a direct substitution of the three spectral reflectance bands to achieve an estimate of the wavelength of the point of maximum absorption. The method is shown to be stable across different sampling regimes and therefore across different hyperspectral instruments. The results show it is possible to accurately estimate the wavelength of spectral absorption features to an RMSE of ±3.8nm in the 2000–2500nm spectral region over multiple sampling intervals and resolutions in sensors with signal-to-noise greater than 500:1. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

A workflow incorporating hyperspectral reflectance data, hull corrections, absorption feature extraction and clustering is presented. The workflow is applied to dense hyperspectral datasets, as collected by hyperspectral drill core logging systems. The extracted absorption features of the reflectance spectra collected from drill cores are shown to form assemblage clusters when plotting the wavelength position of the first, second and third deepest absorption features in two and three dimensions. Using an unsupervised clustering method to establish clusters based on the extracted absorption features yields viewable down hole distributions of similar mineral assemblages. The proposed workflow has the potential for the rapid identification of differing lithologies, alteration and/or weathering overprints. Application of the workflow with no a-priori assumptions about the composition of the potential mineral assemblages provides a means of generating an informative overview of the dataset that is not biased or constrained by preconceptions. The workflow can easily be added to the current workflows of geologists whom are working with dense hyperspectral data to provide an overview of the potential down hole mineral assemblages and aid in the visual logging process or assist in quickly identifying areas for more detailed observation. Furthermore, key mineralogical parameters for resource characterisation, such as the presence of clay minerals can be assessed in a cost and time efficient manner. The proposed workflow is applied to spectra collected from four different drill cores collected in the Gawler Craton located in South Australia and demonstrates the potential outlined above. [ABSTRACT FROM AUTHOR]

Remotely sensed hyperspectral datasets were integrated with petrographic data to map the distribution of sedimentary rocks in order to infer grain size variations within the siliciclastic, Paleoproterozoic Bresnahan Group in Western Australia. Finer sandstones have greater compositional variation compared to coarser sandstones, with higher modal proportions of mudstone intraclasts, K-feldspar, and muscovite laths, and lower modal quartz. Partial Least Squares modelling indicates a link between visible to shortwave infrared spectral data collected on samples and their average grain size. Specific electronic absorptions are important for defining this relationship, particularly in the blue-green visible spectra, wavelengths related to water or hydroxyl bonds, along with certain wavelengths in the shortwave infrared (SWIR) spectra. The results from field samples were compared to airborne hyperspectral datasets which showed broad scale regional variations in composition could be discerned from processed white mica abundance maps and images that use spectral bands 2350 nm and 2200 nm. The remotely sensed compositional variations are relatable to changes in sandstone grain size. Diagenetic alteration and surface weathering may influence the absorption spectra, although the effect of the latter can be reduced by using processed white mica abundance maps. Overall, the results show that airborne hyperspectral datasets, particularly the SWIR part of the spectra, can be useful to remotely map spatial compositional variations associated with sandstone grain size. This shows the method can be used to remotely map siliciclastic successions in other sedimentary basins by aiding recognition of grain size trends and significant stratal surfaces associated with changes in composition. However, the important wavelengths may differ due to other controls on sandstone composition such as uplift history of the source region, changes in sediment dispersal, and transport mechanisms. • Sample spectral data detect compositional change linked to sandstone grain size. • Compositional change with grain size is detected in airborne spectral data. • Study indicates grain size of siliciclastic successions can be remotely inferred. [ABSTRACT FROM AUTHOR]

The use of Shortwave Infrared (SWIR) and Thermal Infrared (TIR) hyperspectral data in mineral exploration has been well documented in many mineralisation types, but is limited in komatiite-hosted nickel sulphide deposits. This project combines hyperspectral, Portable X-ray Fluorescence (pXRF) and whole-rock geochemical data to assess different analytical techniques in the exploration of these deposits. We use the Fisher East nickel sulphide prospects, Western Australia for our case study. The Fisher East prospects lie in an area of the eastern goldfields that has historically been underexplored and understudied. The rocks have undergone intense deformation with primary igneous textures being destroyed, along with strong alteration to talc carbonate assemblages. Combining different analytical tools allowed for differentiation of A and B-zones of original komatiite flows, and the reconstruction of original volcanological facies in a setting where whole rock chemistry as well as igneous textures have been substantially modified by metamorphism. By using different lithogeochemical techniques including pXRF, this study shows the Fisher East prospects are hosted within channelised komatiite flows, and have similar characteristics to Kambalda style deposits. [ABSTRACT FROM AUTHOR]

Abstract: Quantitative iron (oxyhydr-)oxide (Fe-Ox), AlOH-clay and carbonate abundance maps of the Rocklea Dome in Western Australia have been derived from hyperspectral visible-near to shortwave infrared (VNIR–SWIR) airborne data that were compensated for the influence of vegetation cover. The quantitative mineral maps were validated against field data, including ~5500 VNIR–SWIR spectra and ~300 portable X-ray fluorescence measurements. The error on these airborne mineral abundance estimates averages 13.4wt.% Fe for the Fe-Ox abundance, 4.0wt.% Al2O3 for the AlOH-clay abundance and 0.025 for the 2320D parameter used to quantify the carbonate abundance. The unmixed quantitative mineral abundance maps improve geological mapping, including characterisation and exploration for channel iron deposits (CID). In particular, some areas with outcropping CID, which appear subeconomic from the airborne Fe-Ox abundance map without vegetation removal, show as potentially economic CID resources when the influence of vegetation cover is unmixed from the airborne hyperspectral data. These results show that seamless maps of mineral contents can be achieved using data collected from both proximal (drill core and field) and remote (airborne and satellite) hyperspectral sensing systems. [Copyright &y& Elsevier]