Spectral Profiles to Minerals Identification: An Integrated Hyperspectral vs Multispectral Minerals Exploration of the Ophiolitic Belt of Qilla Saifullah District, Baluchistan
Keywords:
Ophiolites, Hyperspectral, Multispectral, Diagnostic Absorption Features, Alteration Minerals, USGS Spectral LibraryAbstract
Baluchistan, the largest province of Pakistan, hosts abundant metallic and non-metallic mineral resources, particularly copper, gold, chromite, lead-zinc, and rare earth elements, making it a strategic region for mineral exploration and geological characterization. Despite such potential, mineral exploration in the province’s ophiolitic belts remains limited by sparse ground surveys, logistical challenges, and incomplete spatial coverage. To address this gap, the present study aimed to (1) Key ophiolitic minerals (chromite, serpentine, magnesite) and associated lithologies with high spectral precision, and (2) Compare hyperspectral and multispectral sensors for mineral identification and mapping. The methodology integrated ZiYuan-1 02D (ZY-1E) hyperspectral satellite data (spectral range 0.4–2.5 µm) with advanced spectral analysis techniques i.e. Diagnostic Absorption Feature extraction, Spectral Matching against the United States Geological Survey (USGS) Spectral Library, and multiple classifiers including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), Random Forest (RF), and targeted band ratios/indices. Mineral point data and lithological maps from the Geological Survey of Pakistan (GSP) were used for accuracy assessment. For comparative analysis, multispectral datasets from ASTER, Landsat-8 OLI, and Sentinel-2 MSI were processed, with a focus on the efficacy of SWIR coverage for mineral detection. Results indicated that ZY-1E hyperspectral data achieved 81.82% mineral classification accuracy and 86.11% lithology mapping accuracy, with Band Ratio techniques emerging as a rapid detection tool. Among multispectral datasets, ASTER outperformed Landsat-8 and Sentinel-2 due to its six SWIR bands, enabling superior discrimination of OH-, Al-, and carbonate-bearing minerals. The study concludes that hyperspectral imagery, due to its high spectral resolution, is indispensable for precise mapping of minerals and lithology in rugged, inaccessible terrains. However, ASTER remains a cost-effective alternative for targeted mapping of alteration minerals where hyperspectral coverage is unavailable. It is recommended to integrate hyperspectral mapping in strategic exploration campaigns to accelerate mineral resource assessment in underexplored regions of the world.
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