Identifying copper deposits in Jordan using integrated approach of reflectance spectroscopy and high spatial remote sensing data

This is the first study that WorldView-2 (WV-2) and Pléiades Neo 3 (PN3) data have been used for mapping copper mineralisation in the Feynan region. The study area is known for its abundant copper deposits, longstanding mining history, and metallurgical activity. Copper mineralisation is found in sandstone, shale, and dolomitic limestone rocks. The collected samples were analysed using X-ray diffraction, X-ray fluorescence, and Atomic Absorption Spectroscopy. The laboratory spectral measurements (0.4–2.5 µm) were carried out to identify diagnostic absorption features of ore samples and create spectra libraries for these ores. Brovey, Gram-Schmidt, and Colour Normalised (CN) spectral sharpening methods, were applied to enhance the spatial resolution and improve spectral separability of WV-2 and PN3. Copper concentrations in mineralised samples ranged up to 6.124%, while XRD confirmed the presence of malachite and azurite as significant copper ore minerals. Gram-Schmidt demonstrated superior efficiency in identifying copper deposits than other pan-sharpening techniques. The neural network and supportive vector machine methods achieved high overall accuracy and Kappa index for the classified images of copper-host rocks. The study’s findings indicate that remote sensing can effectively produce large-scale maps for copper mineralisation, presenting a cost-efficient method for future mining projects in Jordan.