Measurement of the hematite:goethite ratio using field visible and near‐infrared reflectance spectrometry in channel iron deposits, Western Australia

Cudahy, Thomas; Ramanaïdou, Erick

doi:10.1080/08120099708728322

Cited by 69 publications

(46 citation statements)

References 31 publications

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“…The ferric oxyhydroxide minerals, goethite and hematite (and their amorphous, hydrous equivalents, commonly called 'limonite') have strong electronic absorptions in the VNIR spectral region, including crystal field feature that ranges from 0.87 µm for hematite to 0.93 µm for goethite [70] (Figure 5c). …”

Section: Hydrothermal Alteration Mineral Mapping Methodsmentioning

confidence: 99%

Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China

Zhang

et al. 2016

Remote Sensing

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Abstract:One of the most important characteristics of porphyry copper deposits (PCDs) is the type and distribution pattern of alteration zones which can be used for screening and recognizing these deposits. Hydrothermal alteration minerals with diagnostic spectral absorption properties in the visible and near-infrared (VNIR) through the shortwave infrared (SWIR) regions can be identified by multispectral and hyperspectral remote sensing data. Six Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands in SWIR have been shown to be effective in the mapping of Al-OH, Fe-OH, Mg-OH group minerals. The five VNIR bands of Landsat-8 (L8) Operational Land Imager (OLI) are useful for discriminating ferric iron alteration minerals. In the absence of complete hyperspectral coverage area, an opportunity, however, exists to integrate ASTER and L8-OLI (AO) to compensate each other's shortcomings in covering area for mineral mapping. This study examines the potential of AO data in mineral mapping in an arid area of the Duolong porphyry Cu-Au deposit(Tibetan Plateau in China) by using spectral analysis techniques. Results show the following conclusions: (1) Combination of ASTER and L8-OLI data (AO) has more mineral information content than either alone; (2) The Duolong PCD alteration zones of phyllic, argillic and propylitic zones are mapped using ASTER SWIR bands and the iron-bearing mineral information is best mapped using AO VNIR bands; (3) The multispectral integration data of AO can provide a compensatory data of ASTER VNIR bands for iron-bearing mineral mapping in the arid and semi-arid areas.

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Section: Hydrothermal Alteration Mineral Mapping Methodsmentioning

confidence: 99%

Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China

Zhang

et al. 2016

Remote Sensing

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“…Applications now routinely include direct mineralogical mapping and characterisation of soils and sediments, weathering profiles (e.g. laterites) and of ore systems, such as iron ore deposits (Kosmas et al 1984;Tamish et al 1987;Townsend 1987;Hauff & Thiry 1991;Cudahy & Ramanaidou 1997;Madeira et al 1997;Malengreau et al 1997;Scheinost & Schwertmann 1997;Madejová et al 2002;Crowley et al 2003;. Recent advances in instrumentation hardware have seen the development of automated spectral scanning systems, such as CSIRO's HyLogging TM systems, which enable rapid, very high-volume spectral analysis of diverse sample media including drill core, chips and pulps (Ramanaidou et al , 2005Huntington 2005).…”

Section: Introductionmentioning

confidence: 99%

Quantification of Ni laterite mineralogy and composition: a new approach

Wells

Chia

2011

Australian Journal of Earth Sciences

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Quantification of the chemical and mineralogical composition of Ni-bearing laterites is challenged by their complex nature, with the distribution of Ni and other metals controlled by a number of phases. A new approach to predict the Ni (and Fe, Mg) composition of Ni laterites more reliably was tested using samples from drill holes from the Siberia North and Highway deposits. These deposits, selected as examples of (siliceous) oxide-style lateritic deposits, form part of the Kalgoorlie Nickel Project (KNP) in the north-eastern Yilgarn, Western Australia. Diffuse reflectance spectra over the 380-2500 nm wavelength range, measured using the CSIRO HyChips TM automated scanning system, were integrated with a multi-element dataset for 1 m-composite pulp samples using partial least-squares regression (PLSR) analysis. PLSR cross-validation models were developed to predict Ni, MgO and FeO, contents in samples with bulk composition limits of 40.08 wt% Ni and 56 wt% MgO. Calibration and validation models showed a strong, linear trend for characterising FeO and, to a lesser extent, Ni content, whereas reflectance spectroscopic-chemical models for predicting MgO content were less reliable. This reflected the prevailing mineralogy and associated element distribution within the oxide laterite profiles. For example, Fe and Ni distribution is controlled by relatively few mineralspredominantly goethite and, to a lesser extent, the Fe 3þ -bearing smectite, nontronite. Magnesium is associated with a range of Mg-bearing minerals, some of which are compositionally complex and include serpentine, talc, chlorite, smectite and carbonates (e.g. dolomite and magnesite). The MgO abundance alone does not reflect the varied mineralogy of samples with relatively high MgO contents, which can be spectrally distinct. Hence, samples with similar Mg contents, although comprising Mg-bearing minerals with distinct reflectance spectra, were difficult to model (e.g. smectite vs Mg carbonates). The findings of this study demonstrate that characterisation of Ni laterite chemistry may be achieved as part of routine logging of either drill cuttings or diamond drill core using PLSR analysis, but a detailed understanding of the mineral-element association is essential for reliable predictive analysis.

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“…However, particle size and shape, and physicochemical properties exercise an influence on the spectral absorption (Hunt et al 1971, Morris et al 1985. The most notable change is the overall increase in reflectance or albedo with decreasing particle size for goethite and hematite (Cudahy & Ramanaidou 1997, Ramanaidou et al 2008.…”

Section: Spectral Characterization Of Materialsmentioning

confidence: 99%

Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil

et al. 2016

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ABSTRACT:Mapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/ OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in openpit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLIderived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas. KEYWORDS:Remote sensing; Multispectral and hyperspectral imagery; Iron ore. RESUMO: Métodos de mapeamento para óxidos de ferro e argilas, aplicados em imagens Landsat-8/Operational Land Imager (OLI) e Earth Observing 1 (EO-1)/Hyperion e integrados com dados aerogeofísicos, foram testados nos depósitos de ferro de N4, N5 e N4WS, Serra

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Measurement of the hematite:goethite ratio using field visible and near‐infrared reflectance spectrometry in channel iron deposits, Western Australia

Cited by 69 publications

References 31 publications

Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China

Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China

Quantification of Ni laterite mineralogy and composition: a new approach

Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil

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