Hyperspectral Image Spectroscopy (HIS) has revolutionized the spectral interpretation of minerals by providing non-destructive, high-resolution spectral data for precise mineral identification and mapping. This study explores the application of HIS in determining the wavelength of minimum reflectance, a critical spectral parameter for distinguishing minerals based on their unique absorption features. Wavelength mapping using HIS enhances the accuracy of mineral classification and spatial distribution analysis, making it a valuable tool in geological exploration and remote sensing applications. Compared to traditional analytical techniques such as X-ray Diffraction (XRD) and X-ray Fluorescence (XRF), HIS offers a rapid, large-scale, and non-invasive means of mineral characterization. While XRD is highly precise in identifying crystalline structures and phase compositions, it requires physical samples and extensive laboratory preparation. XRF, on the other hand, is effective in determining elemental compositions but lacks the capability to directly identify mineral phases. In contrast, HIS enables remote, high-throughput mineral discrimination based on spectral signatures, making it particularly advantageous for field-based exploration, planetary studies, and resource assessment. The integration of HIS with XRD and XRF provides a comprehensive approach to mineral characterization, leveraging the spectral mapping capabilities of HIS alongside the structural and elemental insights offered by XRD and XRF. This synergy enhances the accuracy of geological interpretations and supports advanced mineral exploration and environmental studies. This study was focused on the analysis of a lithium pegmatite rock sample and the findings underscore the growing importance of hyperspectral data in complementing conventional mineralogical techniques for more efficient and precise geoscientific analyses. The minerals that were identified from the sample included; Lepidolite, Muscovite, Topaz, Quartz and Albite.

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