Although field investigations constitute the cornerstone of geological studies, yet its application is often constrained by limited accessibility, time consumption, and high costs particularly in complex or remote terrains. However, recent advances in remote sensing technologies have significantly improved the ability to map large and inaccessible areas. In this regard, this study presents one of the detailed investigations integrating both optical and radar remote sensing data for the Kerdous and Ait Abdellah inliers in the western Anti-Atlas, Morocco. It aims to evaluate the effectiveness of Landsat 8 OLI and Sentinel-1 SAR datasets for litho-structural mapping, while also providing updated and detailed geological maps for both inliers. Several image processing methods were applied to Landsat 8 data for lithological discrimination, while Sentinel-1 data were used to extract structural lineaments. The results obtained show the effectiveness of PCA in refining lithological outcrops by clearly identifying facies such as quartzite, gabbro, rhyolite, and sedimentary breccias. Also, RGB composites (B2, B5, B7) allowed the visualization of formations like limestone, dolomite, and clay, while band ratio analysis revealed facies such as the Lie-de-vin shales, gabbro, and leucogranite. Moreover, lineament analysis reveals significant tectonic implications, highlighting predominant fault orientations of NE-SW in the Ait Abdellah inlier and NW-SE in the Kerdous inlier. Field verification and correlation with existing geological maps demonstrate this study's contribution to identifying additional geological features, such as recent clay and scree deposits, previously undocumented or poorly represented. The findings highlight the enhanced accuracy and reliability of integrating multisensor remote sensing data for litho-structural mapping, providing a scalable framework for future investigations. However, it should be noted that the main limitations potentially affecting the results are the spatial and spectral resolution of the satellite data and the characteristics of arid and semi-arid terrains.