Geological and Iron Ore Mineralization Mapping Using Remote Sensing Data, Southern Western Desert, Egypt | ||||
| Bulletin of Faculty of Science, Zagazig University | ||||
| Article 16, Volume 2025, Issue 2, June 2025, Page 199-209 PDF (1.08 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/bfszu.2024.331719.1437 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Sara Zamzam   1; Ashraf Ghoneimi 2; Mohamed Hamada Yousef 3; Salah Hanafy 4; Yaseen Aamer 5
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| 1Department of Geology, Faculty of Science, Zagazig University, 44519 Zagazig, Egypt | ||||
| 2Zagazig University, Faculty of Science, Geology Department, 44519, Zagazig, Egypt | ||||
| 3Nuclear Materials Authority, P.O. Box, 530, Maadi, Cairo, Egypt | ||||
| 4Exploration Division, Nuclear Materials Authority, Cairo, Egypt | ||||
| 5Nuclear Materials Authority, P.O. Box 530, Maadi, Cairo, Egypt | ||||
| Abstract | ||||
| Mineral exploration in the southern Western Desert of Egypt presents several challenges, making the process demanding. This difficulty is due to many reasons, such as complex geology sand dunes, inaccessibility, and environmental conditions. Therefore, the current study was done to overcome some of these barriers in the future. West of Gabal Kamil is one of the areas where iron mineralization is present, but it does not receive as much attention as other areas. Consequently, remote sensing techniques were used in this study because they facilitate the quick and cost-effective mapping of surface geological and mineralogical characteristics. Multiple satellite image processing techniques were employed on Landsat8 OLI data, such as band-ratio, principal component (PC) analysis, and maximum likelihood classification (MLC) methods. The region mainly comprises Precambrian basement rocks, such as gneiss and granite. The discovered iron ore strata are intermingled with gneissic rocks and display a striped pattern oriented toward the northeast. The mineralization bands are affected by folding and shearing, which are related to thrust faulting structural elements. The central part of the investigated area was identified as the most promising zone for detailed field studies, exploration, and upcoming prospecting. This study reveals the effectiveness of Landsat8 OLI image in identifying new iron ore regions and delineating the lithological units. The methods can be successfully used to discover new extractable iron ore deposits in arid landscapes. | ||||
| Keywords | ||||
| Iron ore mineralization; Landsat8 OLI; Gabal Kamil; Promising areas | ||||
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