In geological exploration, distinct minerals exhibit diagnostic absorption features driven by electronic transitions of metal ions and vibrational overtones of hydroxyl (OH), water (H₂O), and carbonate (CO₃) functional groups in their crystal lattices. These features manifest across the visible to near-infrared (400–1000 nm), short-wave infrared (1000–2500 nm), and thermal infrared (8–12 μm) regions. For instance, iron-bearing minerals (hematite, goethite, jarosite) display characteristic Fe³⁺ and Fe²⁺ absorption features in the 400–600 nm and 800–1000 nm intervals. Clay minerals (kaolinite, illite, smectite) exhibit distinct Al-OH, Mg-OH, and Si-OH absorption profiles near 1400 nm, 1900 nm, and 2200 nm. Carbonate minerals (calcite, dolomite) present diagnostic combination bands of the CO₃ functional group in the 2300–2350 nm window, while silicate minerals such as quartz and feldspar display characteristic Si-O bond emission or absorption features in the thermal infrared band. Full-spectrum hyperspectral imaging systems cover these extensive intervals simultaneously to construct comprehensive mineral spectral fingerprint libraries, supplying a thorough spectral data foundation for mineral discrimination and alteration zonation research. The HG-HyperUAV full-spectrum hyperspectral imaging system, developed by Hagorun Technology Limited, features a spectral range spanning the VNIR to SWIR bands, meeting multi-scale geological survey requirements ranging from laboratory core scanning to drone-based field mapping. The workflow for hyperspectral data-driven mineral identification typically encompasses spectral preprocessing, endmember extraction, spectral matching, and abundance inversion. Preprocessing includes radiometric calibration, reflectance conversion, denoising, and continuum removal to enhance the identifiability of target absorption geometries. Endmember extraction algorithms, such as the Pixel Purity Index (PPI) and Vertex Component Analysis (VCA), automatically isolate diagnostic endmember spectra from the hyperspectral data cube for automated cross-matching against standardized reference libraries (e.g., USGS, JPL, and ASTER spectral libraries). Spectral matching methods, including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and binary encoding, compute spectral similarity metrics to rapidly classify mineral species. Compared with traditional polarized light microscopy and X-ray diffraction (XRD) analyses, full-spectrum hyperspectral imaging offers non-destructive, rapid (seconds for discrete spot measurements and minutes for area scans), and spatially continuous coverage, making it exceptionally suited for wide-area geological mapping and alteration zonation research.

Hydrothermal alteration zonation serves as a critical vectoring indicator for locating concealed orebodies. The systematic spatial arrangement of distinct alteration assemblages (sericitic, chloritic, silicic, carbonate, and potassic) typically maps paleofluid migration pathways and mineralization centers. Utilizing full-spectrum hyperspectral imaging systems to continuously scan drill cores, outcrops, or exploration line profiles resolves characteristic mineral absorption profiles to automatically delineate alteration mineral distribution logs and zonation boundaries. For example, in a classic porphyry copper deposit system, the alteration sequence vectors outward from the core zone via potassic → phyllic (quartz-sericite) → argillic → propylitic zones. The spectral assemblages of key diagnostic minerals across these zones exhibit sharp contrasts, enabling the core scanning system to rapidly log the exact depths, intervals, and true thicknesses of individual alteration facies. Regarding the quantification of alteration intensity, relative mineral abundance inversion derived from hyperspectral data arrays provides quantitative metrics for resource prospective evaluation. Applying spectral unmixing algorithms—such as the Multiple Endmember Linear Spectral Mixture Model (MESMA) or sparse unmixing—estimates the relative fractional coverage of diverse alteration phases down the core axis or across the terrain surface to generate continuous mineral abundance curves. Correlating these curves with trace-element geochemistry grids constructs statistical relationships between alteration indices (such as illite crystallinity or chlorite composition chemistry) and mineral grade variations, guiding strategic drill target optimization. The HG-HyperUAV full-spectrum hyperspectral imaging system from Hagorun Technology Limited supports an expansive suite of spectral matching and abundance inversion algorithms, exporting precise mineral classification maps and relative abundance logs optimized for automated core digitization and alteration vectoring across exploration fields. In hyperspectral remote sensing geological mapping, drone-mounted or ground-based hyperspectral deployments rapidly capture alteration mineral distribution maps across a survey area. This allows investigators to isolate mineralization-associated alteration zones (such as sericitic, argillic, and pyrophyllitic alterations), narrowing down prospecting targets and elevating exploration efficiency.

Drill cores represent invaluable physical assets in geological exploration. However, traditional core storage and management facilities struggle with massive spatial footprints, physical core weathering/fragmentation, and low information extraction efficiency. Full-spectrum hyperspectral imaging provides a stable solution for core digitization and long-term asset preservation. By capturing co-registered hyperspectral reflectance imagery and calibrated data streams, physical core trays are transformed into digital core assets embedded with spatial coordinates and spectral attributes, archived within relational databases paired with interactive visual platforms. Geologists can remotely query, browse, and re-evaluate historical core metrics across exploration regions, minimizing physical core handling and extending the operational lifespan of the archive. The HG-HyperUAV full-spectrum hyperspectral imaging system from Hagorun Technology Limited balances laboratory-grade spectral resolution with high-throughput batch scanning workflows, delivering a practical tool for exploration entities to build digital core repositories. In mine environmental monitoring, full-spectrum hyperspectral imaging can be deployed for the rapid assessment of tailings compositions, acid mine drainage (AMD), and heavy metal plume propagation. Tailings surfaces exhibiting varying oxidation states display sharp spectral contrasts: fresh tailings appear lighter with higher overall reflectance, whereas oxidized iron minerals (pyrite oxidizing to goethite/limonite) cause a distinct reflectance drop in the 400–600 nm window and an enhanced absorption feature in the 800–1000 nm region. Mapping these oxidation facies via hyperspectral imagery allows analysts to estimate oxidation depth and acid-generating potential. For streams and wetlands impacted by acid mine drainage, hyperspectral imaging can resolve diagnostic absorption profiles of secondary iron minerals (schwertmannite, goethite, ferrihydrite) in precipitates, assisting in delineating pollution boundaries and managing neutralization treatment demands. In the study of spectral responses under plant heavy metal stress, full-spectrum hyperspectral imaging measures the reflectance spectra of canopies surrounding mining zones. This isolates key biophysical parameters, including chlorophyll content, red-edge positions, and moisture indices, evaluating the severity of heavy metal stress on vegetation and providing an automated diagnostic workflow for mine ecological restoration.

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