Optimizing ASTER and PRISMA data for lithological mapping and mineral detection in NW Pakistan

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Remote sensing is a fundamental tool in mineral exploration and lithological mapping. The northern mountainous belt of Pakistan has significant mineral deposits, although hyperspectral data remain underutilized in this region. This study applied an integrated techniques, including principal component analysis (PCA), independent component analysis (ICA), minimum noise fraction (MNF), spectral angle mapper (SAM), mahalanobis distance (MD), spectral index (SI) and support vector machine (SVM) to ASTER and PRISMA data for mapping lithological units and alteration zones in the Garam Chashma region of northwest Pakistan. These approaches successfully isolated target signals, delineated lithological units and mineralization zones, and demonstrated a strong spatial correlation with ground observations and known Cu-Fe mineralization. Field validations and laboratory analysis confirm the remote sensing results and additional identified potential areas near Garam Chashma town, including Momi village, along Arkari Gol and west of the Drunil area. The results supports the reliability of the adopted methodology for minerals exploration globally.