<p>Through the application of spectral analysis to identify minerals that have undergone hydrothermal alteration, remote sensing has emerged as a vital technique in mineral exploration. It is still difficult to map mineral zonation and differentiate overlapping alteration signs in geologically complicated terrains. The objective of this study is to use Landsat 8 (L-8) OLI and ASTER data that correlate to USGS mineral spectral libraries to identify lithological units and hydrothermal alteration zones in the Kafta Humera, Ethiopia. According to the study, combining band ratios, Principal Component Analysis (PCA), Selective PCA (SPCA), and Maximum Likelihood Classification (MLC) with spectral curve comparisons yields detailed lithological mapping and effectively improves the detection of argillic, phyllic, and propylitic alterations. Key findings include high MLC classification accuracy (80.82%) with a kappa coefficient of 0.78, excellent spectral consistency between ASTER and USGS mineral curves, and successful discriminating of alteration minerals using L-8 band ratios (e.g., 6/7 for clays, 4/2 for ferric iron). Alteration zones were effectively identified using PCA and SPCA outputs, however PC5 worked best for mapping structural lineaments. The existence of kaolinite, sericite, chlorite, goethite, and related sulfide minerals in altered rocks was verified by petrographic analysis. These findings show that spectral and statistical methods in conjunction with remote sensing offer a dependable, non-invasive method for mineral discovery in places with restricted ground access. In addition to highlighting the usefulness of multi-sensor analysis in hydrothermal mapping, the study suggests that future mineral prospecting endeavors in comparable geological settings incorporate high-resolution hyperspectral data and field validation.</p>