Multisensor Satellite Data and Field Studies for Unravelling the Structural Evolution and Gold Metallogeny of the Gerf Ophiolitic Nappe, Eastern Desert, Egypt

Abstract

The gold mineralization located in the southern Eastern Desert of Egypt mostly occurs in characteristic geologic and structural settings. The gold-bearing quartz veins and the alteration zones are confined to the ductile shear zones between the highly deformed ophiolitic blocks, sheared metavolcanics, and gabbro-diorite rocks. The present study attempts to integrate multisensor remotely sensed data, structural analysis, and field investigation in unraveling the geologic and structural controls of gold mineralization in the Gabal Gerf area. Multispectral optical sensors of Landsat-8 OLI/TIRS (L8) and Sentinel-2B (S2B) were processed to map the lithologic rock units in the study area. Image processing algorithms including false color composite (FCC), band ratio (BR), principal component analysis (PCA), minimum noise fraction (MNF), and Maximum Likelihood Classifier (MLC) were effective in producing a comprehensive geologic map of the area. The mafic index (MI) = (B13-0.9147) × (B10-1.4366) of ASTER (A) thermal bands and a combined band ratio of S2B and ASTER of (S2B3+A9)/(S2B12+A8) were dramatically successful in discriminating the ophiolitic assemblage, that are considered the favorable lithology for the gold mineralization. Three alteration zones of argillic, phyllic and propylitic were spatially recognized using the mineral indices and constrained energy minimization (CEM) approach to ASTER data. The datasets of ALSO PALSAR and Sentinel-1B were subjected to PCA and filtering to extract the lineaments and their spatial densities in the area. Furthermore, the structural analysis revealed that the area has been subjected to three main phases of deformation; (i) NE-SW convergence and sinistral transpression (D2); (ii) ~E-W far field compressional regime (D3), and (iii) extensional tectonics and terrane exhumation (D4). The gold-bearing quartz veins in several occurrences are controlled by D2 and D3 shear zones that cut heterogeneously deformed serpentinites, sheared metavolcanic rocks and gabbro-diorite intrusions. The information extracted from remotely sensed data, structural interpretation and fieldwork were used to produce a gold mineralization potential zones map which was verified by reference and field observations. The present study demonstrates the remote sensing capabilities for the identification of alteration zones and structural controls of the gold mineralization in highly deformed ophiolitic regions.

Predictive Prospecting Using Remote Sensing in a Mountainous Terrestrial Volcanic Area, in Western Bangongco–Nujiang Mineralization Belt, Tibet

“…Radar has been widely used in geological interpretation by virtue of its strong penetrating power through clouds and its advantage in providing rich texture information, which can identify tectonic information concerning Quaternary rock and loose sediments, to shallow depths in the subsurface [45,46]. The GRD images of Sentinel-1 in terrestrial acquisition pattern IW were used in this study.…”

Chromite-Bearing Peridotite Identification, Based on Spectral Analysis and Machine Learning: A Case Study of the Luobusa Area, Tibet, China

“…Principal component transformation is a statistical technique that selects uncorrelated linear variables called principal components (PC) using orthogonal transformation of a set of possibly correlated variables [12,48,61,69,[80][81][82]. It is one of the most effective and commonly used image information extraction methods in remote-sensing geology [12,48,61,69,[80][81][82]. It generates very small and easily interpretable independent components through linear transformation and preserves the main information [12,48,61,69,[80][81][82].…”

“…It is one of the most effective and commonly used image information extraction methods in remote-sensing geology [12,48,61,69,[80][81][82]. It generates very small and easily interpretable independent components through linear transformation and preserves the main information [12,48,61,69,[80][81][82]. The first principal component includes most of the information of the original multispectral image, and selecting three transformed principal components for the false color composite can achieve the purposes of data compression and highlighting of target information.…”

Multiscale (microscopic to remote sensing) preliminary exploration of auriferous-uraniferous marbles: A case study from the Egyptian Nubian Shield

“…The globally increasing demand for Au and U, and the advances in metallurgical technologies for ore exploration and exploitation strongly revive mineralogical studies in brownfields and small-scale widely distributed economic deposits. Moreover and with the advent of higher spatial resolution remote sensing datasets, accurate lithological mapping could be achieved 36 – 43 even for small-scale rock bodies. Supplementing remote sensing data with machine learning algorithms (MLAs) helps in predicting a certain class (rock type) based on its labeled data in what is known as supervised classification 39 , 44 – 49 .…”