Study on Hyperspectral Mineral Classification Based on Preliminary Mineral Classification System

Hyperspectral remote sensing technology, with its ability to acquire continuous and fine-scale spectral information, shows potential in mineral classification but faces technical challenges such as spectral variability within the same material and spectral similarity among different materials. In previous work, we explored rock classification using various hyperspectral classification methods; however, many minerals were found to exhibit inherently similar spectral signatures, which limited the classification performance of these methods. In this study, we aim to address this issue by constructing a preliminary mineral classification system using laboratory hyperspectral data to redefine categories from a spectral perspective. Specifically, minerals are reorganized into new classes based on their spectral curve characteristics rather than traditional mineralogical definitions, thereby establishing a spectrally driven framework for evaluating separability among spectral groups. A total of 250 mineral specimens were imaged in a darkroom environment using shortwave infrared bands to obtain high-resolution spectral data. After preprocessing, minimum noise fraction (MNF) transformation was applied for dimensionality reduction. Based on their spectral curve characteristics, the 250 mineral specimens were reclassified into 33 spectrally defined preliminary groups. Then, support vector machine (SVM) and random forest (RF) were applied to compare the classification performance of the original individual mineral identification task and the spectrally defined group task, using accuracy, Kappa, and metrics calculated for each class. The experiments demonstrate that the classification scheme based on 33 spectral groups improves classification performance among groups and partially reduces the spectral confusion occurring in the original individual mineral identification task. This framework offers new insights for laboratory-scale mineral research and provides a preliminary experimental basis for future testing under field and airborne/spaceborne conditions.