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Using multispectral and radar remote sensing data for geological investigation, Qena-Safaga Shear Zone, Eastern Desert, Egypt

In the present study, Qena-Safaga Shear Zone (QSSZ) has been the subject matter of detailed remote sensing investigation using Landsat-8, ASTER, and SRTM DEM data. Gathering information from these sensors allowed revealing the different lithological, geological, and structural features. Field observ...

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Bibliographic Details
Published in:Arabian journal of geosciences 2021-06, Vol.14 (11), Article 997
Main Authors: Kamal El-Din, Gamal M., El-Noby, Eman, Abdelkareem, Mohamed, Hamimi, Zakaria
Format: Article
Language:English
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Summary:In the present study, Qena-Safaga Shear Zone (QSSZ) has been the subject matter of detailed remote sensing investigation using Landsat-8, ASTER, and SRTM DEM data. Gathering information from these sensors allowed revealing the different lithological, geological, and structural features. Field observations were carried out to verify the remotely sensed data analysis and interpretation. A fused Landsat-8 OLI and ALOS/PALSAR data clearly improved the view of structural elements that are difficult to be revealed by optical images. The results showed that the area is controlled by the dextral ENE-WSW shearing trend which extends across the Nile at Qena Bend. Lineament analysis and lineament density map demonstrated that the area was subjected to different phases of stress; accordingly, conjugate faults were formed; most of these trends were rejuvenated. The ENE- WSW, NE-SW, and NW-SE are the major tectonic trends affecting the area but the N-S direction is less dominant. WNW, NW, NE, E, and N directions are indicated by sinistral strike-slip movements. The ENE, NE, and WNW are governed by right-lateral strike-slip movements and most of these trends controlled the emplacement of granitoids. The image transformation technique also allowed revealing hydrothermal alteration effects related to the NW-SE and NE-SW fault systems. Overall, combining of multispectral and radar data and field observations is significant for characterizing the geological features in arid regions.
ISSN:1866-7511
1866-7538
DOI:10.1007/s12517-021-07130-2