Mapping iron oxides with Landsat-8/OLI imagery from iron ore deposit in Singhbhum craton, eastern India: Its implication to mineral exploration

Abstract

This research mainly focused on the Kiriburu-Meghahataburu-Bolani iron ore deposit (KMBIOD) in the Singhbhum craton, eastern India, with over 150 million tons of iron ore reserves. By applying Landsat-8/OLI multispectral remote sensing techniques, including band ratio analysis, principal component analysis (PCA), and spectral angle mapper (SAM) classification, the research effectively mapped various types of iron ores. This study employed RGB band combinations of band ratios {4(0.64–0.67 μm)/2(0.45–0.51 μm), 5(0.85–0.88 μm)/7(2.11–2.29 μm), 5(0.85–0.88 μm)/4(0.64–0.67 μm)} and PCA (PC bands 1, 5, and 6; PC bands 4, 5, and 6). These techniques were used to effectively distinguish iron ore from associated lithological units. Specific band ratios (5/7, 4/5, and 4 + 6/5) were instrumental in identifying high-grade and low-grade iron ore zones. PCA was used to provide detailed spectral information, identifying various iron ore types, including low-grade iron ore and clay minerals. The results were validated with spectral analysis and spectral angle mapper (SAM) classification methods, supported by X-ray Diffraction (XRD) analysis of iron ore samples collected during field survey. This integrated remote sensing approach proved effective for mapping iron ore in densely vegetated areas and enhancing geological understanding of mineralized zones. Landsat-8/OLI imagery demonstrated robust performance in iron ore exploration, concluding that these techniques were effective for discriminating and classifying iron ore in the Singhbhum craton and could be applied to similar regions.