Lithological Discrimination and Lineaments Extraction Using Landsat-8 and Sentinel-2A Data, A Case Study of Gabal Abu Hamr and Gabal Abu Kharif Area, North Eastern Desert, Egypt

The current work emphasizes the ability of Landsat-8 (L8) and Sentinel-2A (S2A) satellite data through image processing to discriminate lithology and extract lineaments in the area of Gabal Abu Hamr and Gabal Abu Kharif, Northeastern Desert, Egypt. Different image processing methodologies are utilized to both Landsat-8 and Sentinel-2A images such as False-Color Composites (FCC), analysis as Minimum Noise Fraction (MNF), Principal (PCA), where largest variation recorded is in the first three PC bands (more than 99%), and Independent Component (ICA) and mathematical means as Band Algebra. Furthermore, image classification techniques include Maximum Likelihood (MLC) and Support Vector Machine (SVM) are utilized for identifying pixels with similar characteristics, which support the process of separating rock unites in the current study. These techniques are able to discriminate the rocks of the study area, especially the older granitoid rocks, which are difficult to separate in the field due to the mineral affinity between them. The manual and automatic lineaments extraction methods by visual interpretation and Directional Filtering via the LINE algorithm in PCI Geomatica shed light on the common lineaments directions within the study area exhibiting trends in the NE-SW and E-W, followed by a trend in the N-S direction.