Search Results (171)

Pegmatite-related rare-metal exploration in high-altitude mountainous regions is commonly limited by rugged terrain, complex structural frameworks, and uneven bedrock exposure. This study presents a multi-source remote-sensing workflow for regional-scale rare-metal prospectivity assessment in the Pusharong area of western Sichuan, China, by integrating GF-5A Advanced Hyperspectral Imager (AHSI) data, ASTER thermal infrared (TIR) data, and structural interpretation. GF-5A hyperspectral data were used as the primary source for extracting mineral-related anomaly responses associated with muscovite, tourmaline, cookeite, and spodumene. Mixture Tuned Matched Filtering (MTMF) was applied to enhance weak target-related spectral responses, whereas Spectral Angle Mapper (SAM) provided an independent spectral-consistency constraint to reduce potential over-identification. ASTER TIR-derived Quartz Index (QI) and Feldspar Ratio Index (FRI) responses were used as supplementary lithological and differentiation-related background constraints rather than as continuous quartz–feldspar mineral-distribution maps. Structural interpretation was further integrated to evaluate the spatial relationship between mineral-related anomalies and favourable fault settings. Preliminary point-based validation shows a high degree of consistency between the mapped anomaly zones and available field or geochemical observations, with an overall consistency of 92.86% and a Kappa coefficient of 0.91. The integrated workflow delineated four prospective target zones for follow-up verification, with T1 showing the strongest multi-source support, followed by T2 and T3, whereas T4 is regarded as a lower-priority verification target. These results demonstrate the usefulness of the workflow for first-pass regional target prioritisation in complex mountainous terrain, but the delineated targets require further field, mineralogical, geochemical, and drilling verification before any deposit-scale interpretation can be made. Full article

To reveal the varieties and color genesis of emerald-green tourmaline crystals from Tanzania, a systematic study was conducted using conventional gemological tests, X-ray diffraction, Fourier-transform infrared spectroscopy, polarized ultraviolet–visible spectroscopy (UV–vis), X-ray photoelectron spectroscopy (XPS), low-temperature photoluminescence (PL) spectroscopy, and electron probe microanalysis (EPMA). The results indicate that the tourmaline is dravite. Its UV–vis absorption spectrum shows strong broad absorption bands at approximately 436 and 600 nm, with a pronounced transmission at 520 nm, which directly accounts for its emerald green color. Obvious polarized absorption was observed along and perpendicular to the c-axis. XPS and PL results confirm that chromium is present in the samples in the form of Cr³⁺. EPMA compositional analysis indicated a low Cr₂O₃ content of 0.804 wt.%; combined with crystal structural properties and spectral responses, these results suggest that Cr³⁺ preferentially occupies the Y site in the crystal structure and that d–d electronic transitions represent the underlying mechanism of its color formation. This study comprehensively illustrated the mineralogical and spectral properties of Cr-bearing dravite, providing fundamental data for further research on its genesis and gemological application. Full article

Transitional marine–continental shale reservoirs are typified by intricate pore architectures and pronounced heterogeneity; accurate characterization of their pore network and fluid mobility underpins reservoir appraisal and sweet-spot forecasting. Focusing on the Longtan Formation transitional shales in the Sichuan Basin, this study integrates NMR T₂ spectrometry, geochemical–mineralogical assays and multifractal analysis to elucidate multi-scale heterogeneity of the pore framework and its governing mechanisms. Results reveal that the investigated shales are characterized by low porosity (0.46–7.43%) and high bound fluid saturation (66.77–97.28%). Multifractal spectral width (Δα) and degree of multifractality (ΔD) serve as robust metrics of pore heterogeneity, correlating closely with rock composition (e.g., TOC and clay content). By combining multifractal indices, mineralogical assemblage and fluid movability, the samples are classified into three reservoir archetypes, with Type I (weakly heterogeneous—high quality) identified as the prospective developmental sweet spot. This work provides a theoretical and methodological backbone for quality assessment and play-ranking of transitional marine–continental shale reservoirs. Full article

In the Iberian Pyrite Belt (IPB), long-term persistence of mine waste piles poses environmental challenges. The present work studies the Trimpancho Mining Complex in northern IPB with exposed mine waste and acidic waters in the proximity to the Chança River, a tributary of the Guadiana international river. A multidisciplinary approach is proposed, using hyperspectral reflectance spectroscopy, portable X-ray fluorescence (pXRF), multispectral Unmanned Aerial Vehicle (UAV) and Sentinel-2 images. Spectroscopic, geochemical and remote sensing methods were applied to characterise the mining area. Comparison of hyperspectral data with spectral libraries were used to validate mineralogy. Multispectral UAV data is used for custom band-ratios and adapted to Sentinel-2 images. Results grouped the samples into four groups. Spectroscopy is indicative of clays (white mica and smectite group), hematite/goethite, jarosite, and arsenopyrite and pyrite (exclusive to the Group 2); iron-rich samples reach maximum reflectance earlier than iron-poor samples. Geochemical studies show an increase in content of heavy metal such as As, Cu, Fe, Pb, and Zn from Group 1 < Group 3 ≈ Group 4 < Group 2, but Group 4 showed elevated Pb and Zn. Custom false colour composition highlighted the groups in UAV and satellite, thus constituting cost-effective tools for finding contamination sources. Full article

Phosphate waste rock piles (PWRPs) generated by open-pit phosphate mining are highly heterogeneous and difficult to characterize using conventional point sampling alone, which limits representative resource assessment, selective recovery, and rehabilitation planning. This study develops an integrated framework combining PRISMA spaceborne hyperspectral imagery, ground-based mineralogical analyses, and spatially constrained machine learning to map lithological heterogeneity at the Benguerir phosphate mining site, Morocco. A three-stage spectral optimization workflow, including atmospheric band masking, Savitzky–Golay filtering, and analysis of variance (ANOVA)-based feature selection, was applied to identify the most discriminative Short-Wave Infrared (SWIR) bands for lithological classification. After removing redundant observations located within shared PRISMA pixel footprints, 127 spatially independent samples were retained for model development. Five supervised classifiers (Random Forest, Extra Trees, XGBoost, Support Vector Machine, and K-Nearest Neighbors) were evaluated under a spatially constrained cross-validation framework aligned with the 30 m native PRISMA pixel size. Ensemble-based models, especially Extra Trees and Random Forest, provided the most stable performance, with balanced accuracies of 0.56–0.69 and area under the receiver operating characteristic curve (AUC) values exceeding 0.95 for carbonate-dominated lithologies. Lower discrimination between phosphate and siliceous facies reflects intrinsic mineralogical mixing and spectral overlap at the sensor scale. Entropy-based uncertainty and posterior probability mapping revealed spatially structured prediction ambiguity concentrated along lithological boundaries and transitional zones, consistent with petrographic evidence of compositional heterogeneity. These results indicate that moderate but stable accuracies likely represent realistic performance limits for spaceborne hyperspectral mapping of complex mining environments under spatial constraints. The proposed framework provides a transferable and uncertainty-aware basis for lithological mapping, selective recovery assessment, and sustainable phosphate waste management. Full article

Orogenic gold deposits host a substantial proportion of global gold resources, yet their internal alteration architecture and mineral assemblage variability are commonly reconstructed from random samples, limiting our ability to resolve along-profile zonation and its linkage to gold enrichment. Here we evaluate hyperspectral drill-core spectroscopy, integrated with surface spectroscopy and petrographic validation, as a rapid and spatially continuous approach to delineate alteration zoning in the Liba orogenic gold deposit (West Qinling Orogen, China). We acquired hyperspectral spectra (0.35–2.50 μm) from 255 evenly spaced surface points across two orebodies and from nine representative drill cores scanned at 1 m intervals, and organized the spectral dataset according to Au-grade domains (<0.05 g/t, 0.05–0.5 g/t, and >0.5 g/t). Spectra were quality controlled and interpreted using ENVI-based spectral library matching and The Spectral Geologist (TSG) processing workflows. Petrographic observations from 76 polished thin sections provide independent mineralogical constraints. The hyperspectral results resolve a systematic alteration progression from barren chlorite-dominated assemblages (Au-grade < 0.05 g/t) (locally with minor carbonate) through a weakly mineralized transition (Au-grade 0.05–0.5 g/t) characterized by diminishing chlorite and emergent kaolinite–carbonate with intensified sericitization, to an ore-grade (Au-grade > 0.5 g/t) assemblage dominated by kaolinite–sericite–carbonate–pyrite where biotite persists in distal and proximal zones but was progressively replaced by chlorite during subsequent hydrothermal stages; its modal abundance exhibits a clear inverse correlation with mineralization intensity. These results demonstrate that hyperspectral core scanning, coupled with targeted validation, can rapidly reconstruct a three-dimensional alteration architecture and provide practical mineralogical vectors for exploration targeting and process-oriented studies in orogenic gold systems. Full article

The volcanic island of Fuerteventura (Canary Islands, Spain) offers the opportunity to investigate aqueous alteration in Mars-like environments. As on Mars, landscapes on Fuerteventura are typified by mafic volcanic landforms, minimal precipitation, strong winds, and minimal or absent vegetation. In this study, we perform reflectance spectral and geochemical analysis of near-surface basaltic materials from Fuerteventura’s Gairía caldera, as well as samples from a nearby arroyo. Tephra, outcrop rock, and soil-like material exhibit variations in color, spectral properties, mineralogy, and major oxides. Visible/near-infrared (VNIR) spectra of orange/light-brown materials have higher reflectance values and much stronger features attributed to phyllosilicates (including H₂O and Al-OH bands near 1.41–1.45, 1.91–1.92, 2.21, and 2.76 µm characteristic of montmorillonite in caldera and arroyo samples, plus shoulder features near 1.38 and 2.17 µm and a band at 2.70 µm indicative of kaolinite/halloysite in arroyo samples) compared to black/brown materials. Additionally, several of the highly altered samples contain spectral bands due to calcite at 2.33, 2.53, 3.36, 3.47, and 3.97 µm. Major oxide data reveal similar distinctions between lighter orange/tan (altered) versus darker (unaltered) samples. Lighter and orange-colored samples show elevated Al₂O₃ and depleted Fe₂O_3T, MgO, CaO, and Na₂O, as well as higher chemical index of alteration (CIA) values, overall characteristic of water-soluble cation release (and secondary clay formation) during incipient-to-intermediate chemical weathering of basalt. Gairía weathering trends inform phyllosilicate formation in arid volcanic settings broadly. Of particular interest is the chemical alteration of basalt to montmorillonite and kaolinite/halloysite taking place in warm but water-limited desert conditions, suggesting the potential for clay formation in analogous (warm but relatively dry) paleoenvironments on early Mars. Full article

Soil organic carbon (SOC) plays a critical role in the global carbon cycle and agroecosystem productivity. However, existing hyperspectral inversion models often exhibit significant predictive biases when applied across large geographic scales, primarily due to the spatial heterogeneity of pedogenic environments and background mineralogy. This study proposes a cross-regional SOC prediction method based on an optimal spectral feature set (SOC-OSFS). Leveraging laboratory hyperspectral and SOC data from 17,730 samples collected across the black soil regions of Northeast China and Europe, a core spectral feature set comprising 31 diagnostic bands was extracted using the competitive adaptive reweighted sampling (CARS) algorithm combined with the successive projections algorithm (SPA). Although this SOC-OSFS accounts for merely 1.55% of the original full-spectrum dimensionality (31 out of 2000 bands), it demonstrated robust analytical capability in local modeling across all study regions, yielding coefficients of determination (R² = 0.6714–0.8854). When transferring the prediction model calibrated in the core source domain (n = 10,000) to the other seven independent typical black soil target domains, the direct cross-regional prediction consistently reduced the root mean square error (RMSE) by over 15% compared to that of the full-spectrum models. By further incorporating 20% of the local background samples for intercept correction, the cross-regional predictive accuracy was substantially improved; the goodness-of-fit for the Northeast China target domains increased sharply (maximum R² = 0.8567), and the European target domains, which feature substantially different pedogenic environments, were successfully corrected from negative to positive linear fits. This study validates the efficacy of extracting physiochemically meaningful spectral bands in mitigating the interference caused by spatial heterogeneity, thereby providing a mechanistically grounded and practically viable framework for large-scale SOC estimation via remote sensing. Full article

Gem-quality garnets exhibit significant potential for U-Pb geochronological applications due to their advantageous characteristics, including high closure temperatures (750–850 °C), optical transparency, chemical homogeneity, and low inclusion content. This study focuses on the gem-quality yellow-green grossular garnet variety (commonly termed Mali garnet), a unique gemstone exclusively occurring in contact metamorphic deposits of Western Africa’s Republic of Mali. Despite its mineralogical significance, fundamental aspects, including precise age determination and chromophore mechanisms of Mali garnet, remain poorly constrained. Here, we conducted standard gemological characterization, spectroscopic analyses (UV–Vis, FTIR, and Raman), electron probe microanalysis (EPMA), micro-X-ray fluorescence (μ-XRF) elemental mapping, and in situ trace element and laser ablation U-Pb geochronological analysis on Mali garnets. The spectral data and chemical composition studies reveal that the coloration of Malian garnets is primarily attributed to the presence of iron and chromium. Our U-Pb geochronological results yield a crystallization age of 197 ± 3 Ma for the Mali garnet samples. The robustness of garnet U-Pb systems in preserving crystallization ages through multiple thermal events supports their application to Precambrian polymetamorphic terranes, where zircon systems are frequently reset. Full article

Fourier Transform Infrared Spectroscopy (FTIR) is increasingly used for the mineralogical characterization of complex materials such as ceramics, soils and clays. However, its quantitative application remains limited due to spectral overlapping and matrix effects in solid samples. In this study, a semi-quantitative mineralogical analysis method based on Attenuated Total Reflectance FTIR (ATR-FTIR) is proposed. The method uses the principal absorption band of calcite as a normalization reference in order to estimate relative molar absorptivity coefficients according to the Lambert–Beer law. Experimental spectra obtained from pure minerals and laboratory mineral mixtures were analyzed using derivative spectroscopy and numerical optimization. The correlation between experimental and calculated spectra was performed using the GAMS equation modeling environment and the nonlinear programming solver CONOPT. Mineral mixtures were used to determine the minimum detectable band intensity and detection limits. Bands with normalized intensities lower than 0.01 were discarded, corresponding to a detection limit of approximately 7 mol%. Application of the proposed methodology to ceramic coatings samples from Teruel and Castellón demonstrated that the FTIR spectra are dominated by aluminosilicate bands associated with quartz and clay minerals, together with carbonate features attributable to calcite. These results are consistent with the expected mineralogical composition of ceramic raw materials and confirm the suitability of the method for analyzing natural samples. However, the ATR-FTIR method presents several inherent limitations that may affect both the accuracy and reproducibility of spectral data. Full article

Beryllium (Be), a critical strategic metal element, is predominantly extracted from beryl, which serves as a key mineral combining significant strategic importance with essential industrial applications. Significant debate remains, however, regarding the mineralogical characteristics and color-causing mechanisms of beryl. In this study, we integrate Electron Probe Microanalysis (EPMA), Fourier transform infrared spectrometer (FTIR), laser Raman spectrometer (LRS), X-ray diffractometer (XRD), and ultraviolet–visible spectrophotometer (UV-VIS) to elucidate the mineralogy and spectral characteristics of pegmatitic beryl from Xinjiang, Northwest China. The results indicate that the beryl mainly presents a yellowish-green color, associated with minerals such as feldspar, quartz, and garnet. The EPMA results confirm the chemical composition of the typical beryl and indicate that the Al content is lower than the theoretical value, reflecting the substitution of Al³⁺. The FTIR shows characteristic vibrations of Si-O tetrahedral groups within the range of 1400~400 cm⁻¹, along with distinct bending and stretching vibration peaks of H₂O molecules observed in the range of 1700~1500 cm⁻¹ and 3500~3800 cm⁻¹, respectively. Combined with spectral analysis, it can be determined that both Type I water and Type II H₂O are present in the samples. Raman spectroscopy reveals that the two distinct peaks of beryl are located at approximately 685 cm⁻¹ (attributed to the stretching vibration of Be-O) and 1067 cm⁻¹ (corresponding to the bending vibration of Si-O), respectively. The XRD analysis shows that the ratio of unit cell parameters c/a of the samples ranges from 0.9950 to 1.0068, and the isomorphous substitution in its structure is mainly manifested as the replacement of octahedral coordination sites by Al³⁺. The UV-VIS shows that Fe³⁺ exhibits a broad absorption band in the range of 200~300 nm, while no obvious absorption peaks are observed in the range of 300~800 nm. The above characteristics indicate that Fe³⁺ has a significant impact on the color of beryl. For green beryl samples, a portion of Fe³⁺ occupies the structural channel sites and interacts with H₂O molecules within the channels, which contributes to the yellowish hue of beryl. Our study highlights crucial data for mineralogical identification, genetic tracing, as well as efficient utilization of beryl resources. Full article

To elucidate the influence of water on terahertz (THz) spectral responses, terahertz time-domain spectroscopy (THz-TDS) was employed to monitor the thermal decomposition of copper(II) sulfate pentahydrate in this study. Continuous dehydration of the hydrate induces pronounced variations in the THz signal. At the initial stage of thermal decomposition, these changes primarily originate from the evolving state and amount of water confined within the CuSO₄·5H₂O lattice. After detaching from the crystalline framework, the released water molecules do not evaporate immediately; instead, they transiently reside near the copper sulfate as free water. When the temperature reaches approximately 60 °C, a dynamic equilibrium is established between crystalline water and free water. The THz spectral data reveal that the sample exhibits its strongest THz absorption at this temperature. Consequently, the THz signal during decomposition displays a characteristic trend: an initial decrease followed by an enhancement. These findings demonstrate that THz-TDS represents a promising approach for probing the state and content of water, thereby contributing to the development of a powerful analytical tool for fundamental studies in mineralogy. Full article

Accurate mapping of lunar mineral distributions is essential for understanding the Moon’s origin and evolution and for enabling future in situ resource utilization (ISRU). Yet mineralogical inversion from orbital hyperspectral observations remains challenging due to limited spatial resolution, complex photometric conditions, and sparse returned samples. We present PGU-Net, a Hapke physics-guided deep autoencoder for nonlinear blind unmixing of lunar hyperspectral data. The encoder adopts a dual-attention design to enhance discriminative spectral features. The decoder performs linear mixing in the SSA domain and then reconstructs reflectance through a lightweight nonlinear module, while physics-consistent losses encourage radiative-transfer plausibility. Experiments on a synthetic lunar regolith dataset demonstrate that PGU-Net achieves consistently lower endmember SAD and abundance aRMSE than representative baselines across multiple noise levels. Additional validations on the terrestrial AVIRIS Cuprite benchmark and on Moon Mineralogy Mapper (${\mathrm{M}}^3$) observations near the Chang’e-5 (CE-5) and Chang’e-6 (CE-6) landing regions yield physically plausible mineral distributions. The ${\mathrm{M}}^3$ maps are broadly consistent with Kaguya MI mineral products and returned-sample constraints, supporting the practicality of PGU-Net for lunar mineralogical mapping. Full article

An integrated Visible–Near-Infrared to Shortwave Infrared spectroscopy (VNIR–SWIR spectral), mineralogical, and geochemical study was conducted on the Shadan Au–Cu porphyry–epithermal system in the eastern Lut Block, Iran, to characterize hydrothermal alteration zonation and classify alteration–lithological units. Thirty-eight representative samples were analyzed by reflectance spectroscopy (0.35–2.50 µm), petrography, XRD (X-ray Diffraction), X-ray fluorescence (XRF), and Inductively Coupled Plasma Mass Spectrometry (ICP–MS). Quantitative continuum-removal processing identified diagnostic absorption features near 0.90, 1.40, 1.90, 2.17, 2.20, 2.33, and 2.50 µm, corresponding to Fe³⁺, Al–OH, H₂O, and CO₃ absorptions. Seven alteration–lithological groups (G₁–G₇) were defined and verified by XRD and petrography, representing illite–smectic–kaolinite (argillic), alunite–dickite (advanced argillic), quartz–silicified, Fe-oxide, oxidized argillic, chlorite–epidote (propylitic), and carbonate–iron vein assemblages. Whole-rock geochemical data reveal coherent enrichments of Al₂O₃–K₂O in clay-dominant zones, Fe₂O₃ in oxide-rich areas, and CaO–MgO in carbonate-bearing assemblages. Spectral and geochemical integration delineates a vertically and laterally zoned system evolving from acidic to neutral–oxidizing conditions, typical of low-sulfidation epithermal overprints on porphyry-style magmatic centers. This multidisciplinary framework demonstrates the value of combining VNIR–SWIR spectroscopy with mineralogical and geochemical constraints for vectoring and classification of alteration systems in post-collisional volcanic belts. Full article

We present an innovative, cost-effective framework integrating laboratory Hyperspectral Imaging (HSI) of the Bechar 010 Lunar meteorite with ground-based lunar HSI and supervised Machine Learning (ML) to generate high-fidelity mineralogical maps. A 3 mm thin section of Bechar 010 was imaged under a microscope with a 30 mm focal length lens at 150 mm working distance, using 6x binning to increase the signal-to-noise ratio, producing a data cube (X × Y × $\lambda$ = $791\times 1024\times 224$, $0.24$ mm × $0.2$ mm resolution) across 400 nm to 1000 nm (224 bands, $2.7$ nm spectral sampling, $5.5$ nm full width at half maximum spectral resolution) using a Specim FX10 camera. Ground-based lunar HSI was captured with a Celestron 8SE telescope (3 km/pixel), yielded a data cube ($371\times 1024\times 224$). Solar calibration was performed using a Spectralon reference (99% reflectance < 2% error) ensured accurate reflectance spectra. A Support Vector Machine (SVM) with a radial basis function kernel, trained on expert-labeled spectra, achieved 93.7% classification accuracy (5-fold cross-validation) for olivine (92% precision, 90% recall) and pyroxene (88% precision, 86% recall) in Bechar 010. LIME analysis identified key wavelengths (e.g., 485 nm, 22.4% for M3; 715 nm, 20.6% for M6) across 10 pre-selected regions (M1 to M10), indicating olivine-rich (Highland-like) and pyroxene-rich (Mare-like) compositions. SAM analysis revealed angles from $0.26$ rad to $0.66$ rad, linking M3 and M9 to Highlands and M6 and M10 to Mares. K-means clustering of Lunar data identified 10 mineralogical clusters (88% accuracy), validated against Chandrayaan-1 Moon mineralogy Mapper (${\mathrm{M}}^3$) data (140 m/pixel, 10 nm spectral resolution). A novel push-broom HSI approach with a telescope achieves 0.8 arcsec resolution for lunar spectroscopy, inspiring full-sky multi-object spectral mapping. Full article