Corrado, Francesca (2025) Application of satellite and proximal hyperspectral analysis to district-scale exploration for strategic and critical metals. [Tesi di dottorato]

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Abstract

The increasing demand for critical raw materials (CRMs) has intensified the need for innovative exploration tools capable of identifying mineralization at different scales. In this context, hyperspectral remote sensing offers an alternative, faster and more cost-effective approach for identifying minerals based on their spectral signatures. The present PhD thesis aims to investigate the critical elements (CEs), including lithium and vanadium, in various types of ore deposits by combining traditional and innovative exploration methods in order to delineate alteration footprints and identify vectors to mineralization. Several deposit types worldwide were chosen and investigated, including volcano-sedimentary Li deposit in the United States (McDermitt caldera), V-bearing Zn-Pb mineralization in carbonates (Otavi Mountainland in Namibia and Mibladen deposit in Morocco), as well as U-V deposits in the Paradox Basin (La Sal, Omega and Big Buck mine areas). In order to achieve the objectives of the study, laboratory- and satellite-based sensors were employed in this research, including Headwall Photonics hyperspectral and Specim FX10 and SWIR cameras for sample imaging and the German Aerospace Center’s EnMAP (Environmental Mapping and Analysis Program), the Italian Space Agency’s PRISMA (PRecursore IperSpettrale della Missione Applicativa) and NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) for regional- and district-scale investigations. Data processing followed a workflow designed to identify target absorption features from the analyzed spectra, determine the relative abundances and chemical compositions, and map their spatial distribution using band ratios and minimum wavelength techniques. Several minerals were identified and mapped, such as phyllosilicates (e.g., muscovite, Al-, Fe- and Mg-smectites, illite, kaolinite, chlorite), carbonates (e.g., calcite, dolomite and smithsonite), sulfates (e.g., gypsum), vanadates (e.g., descloizite and mottramite), V-bearing phyllosilicates (e.g., roscoelite) and Li-smectite (e.g., hectorite). Notably, novel spectral signatures for V-illite, V-chlorite, descloizite and mottramite were identified, expanding existing spectral libraries for V-bearing minerals. The result highlights the advantages and limitations of hyperspectral imaging across the various observation scales. EnMAP, PRISMA and EMIT satellite data demonstrated strong potential for identifying diagnostic mineral assemblages and exploration proxies (mappable criteria for mineralogical traps), although their reliability is constrained by spectral overlaps, vegetation cover, surface exposure and sensor resolution. Integrating hyperspectral data with geological and geochemical analysis is therefore essential for accurate mineral characterization and target delineation. Sample-based analyses provided the highest level of accuracy, allowing the identification of uncharacterized spectral minerals (e.g., V-bearing minerals) and the detection of target absorption features for validation of broader datasets. In conclusion, this research demonstrates that combining hyperspectral data with geological and geochemical analyses enables effective mapping of mineral assemblages and identification of vectors to critical element mineralization. While satellite sensors provide regional-scale insights, sample-based analyses remain essential for accurate characterization and validation, highlighting hyperspectral techniques as a powerful, complementary tool for exploration.

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