Abstract
Seafloor massive sulphide (SMS) deposits are hosts to a wide range of economic minerals, and may become an important resource in the future. The exploitation of these resources is associated with considerable expenses, and a return on investment may depend on the availability of multiple deposits. Therefore, efficient exploration methodologies for base metal deposits are important for future deep sea mining endeavours. Underwater hyperspectral imaging (UHI) has been demonstrated to be able to differentiate between different types of materials on the seafloor. The identification of possible end-members from field data requires prior information in the form of representative signatures for distinct materials. This work presents hyperspectral imaging applied to a selection of materials from the Loki’s Castle active hydrothermal vent site in a laboratory setting. A methodology for compensating for systematic effects and producing the reflectance spectra is detailed, and applied to recover the spectral signatures from the samples. The materials investigated were found to be distinguishable using unsupervised dimensionality reduction methods, and may be used as a reference for future field application.
Highlights
Remote sensing with hyperspectral and multi-spectral technologies has seen wide use in prospecting for minerals and hydrocarbons on land [1]
While it is possible to select masks based on distance metrics from a reference pixel (e.g., spectral angle mapping (SAM)), we found that defining connected regions gave a better impression of the inherent variability of the materials
The red overlay is where the signal-to-noise ratio was deemed to be too low for accurate reproduction of the true reflectance, with the same threshold being used for all samples
Summary
Remote sensing with hyperspectral and multi-spectral technologies has seen wide use in prospecting for minerals and hydrocarbons on land [1]. Materials altered through hydrothermal processes may be associated with mineral deposits, and have been a focus of classical multi-spectral imaging such as the Landsat Thematic Mapper (TM). Alunite and hydrothermal clay have distinct reflective and absorptive properties at the wavelengths centred at 1.65 μm (TM5) and 2.215 μm (TM7). Iron oxides and sulphates have low blue reflectance (TM1) and high red reflectance (TM3) in the visible spectrum. The ratios between these pairs have been used to discriminate in prospecting for terrestrial deposits of hydrothermal origin [2]. The discrimination of different materials based on reflective properties using visible/near-infrared imaging spectroscopy (VNIR; 0.4 μm to 1.0 μm) may still be possible [3].
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