الفهرس 
Chapter I IntroductionOnly 14 pages are availabe for public view
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Abstract
The Red Sea governorate is rich in natural resources that create challenges for Egypt’s future economy and growth. The right ways must be found to manage and discover these resources is full of natural resources overexploited by humans and mismanaged by them. So, the right ways must be found to manage and discover these resources without wasting them, ways that seek sustainability while securing the needs of the current and next generation. So, we used geographic Information system and Remote Sensing to study the Natural Resource Management of Red Sea Governorate. The most successful and extensively utilized data for lithologic mapping and exploration targets come from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Operational Land Imager (OLI) sensors. Using Landsat 8 OLI, Land cover was classified, all classification methods were carried out, and the most accurate was selected by doing an accuracy assessment, The image was classified using the supervised classification method. Given that the vast majority of the study area is desert, therefore, we tended to search for mineral resources of high economic value. The images have been processed using the band ratio (BR) technique and false color composite (FCC). The OLI band ratios (6/7, 6/2, 4/5, and 6/5*4/5) have been applied to distinguish between some rocks (metavolcanic, metasedimentary, felsic, and granitic).. The False color composite of Landsat 8 helps us to Improve the Image and Facilitates the Interpretation of Multispectral Satellite Data. The results proved that combining spectral bands identifies potential mineralization points through satellite data. In order to confirm these places, a case study was done for part of the study area using the Aster satellite to increase its accuracy and compare the results with each other, two color ratio composites of Aster were examined in the current study and were shown to be the most effective composites for identifying lithological units and alteration zones. Validation of the results using geological maps showed a good relationship with the location of minerals. The study showed that the most widespread mineral is granite, and by integrating geology and remote sensing, common features were identified that help in identifying uranium within the younger granites in the study area. The method created in this work is time- and money-efficient, and it may be used to gather reliable and current mineral data in inaccessible or new geologically unexplored regions.