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This work aims to apply spectral image processing techniques that have been used often to process hyperspectral data to analyze multispectral ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 8 data for mapping uranium-bearing siliceous rocks within ElMissikat granite. These techniques succeeded effectively in recognition of the same features at El-Eradiya and Gattar granites. Siliceous materials (siliceous sinter), as used here, is a spectral group of SiO 2 minerals including opal, chalcedony and cristobalite derived from hydrothermal fluids and/or the decomposition of granite. The spectral identification of such minerals depend mainly on the uses a hydration absorption feature that characterize some hydrated silica at wavelength region of 2.2to 2.4-μm. The effectiveness of the hyperspectral analysis techniques used to compare a pixel spectrum with the spectra of known pure materials, extracted from the spectral end member selection procedures, including minimum noise fraction (MNF), pixel purity index (PPI) and n-dimensional visualization. Among those of the spectral analysis algorithms employed, spectral angle mapping (SAM) and matched filtering (MF) produced accurate classifications that were close to the ground reference data. The hyperspectral analysis of an ASTER and Landsat 8 dataset covering the studied areas, has successfully effective in detecting lithological units than traditional multispectral analysis procedures. Field validation and laboratory investigation were carried out to prove and support the results obtained from ASTER and Landsat 8 processing. These results succeeded to delineate additional sites of siliceous materials that could be a promising areas to host the uranium mineralization.

nuclear sciences scientific journal 

HYPERSPECTRAL ANALYSIS OF ASTER AND LANDSAT 8 DATA TO CHARACTERIZE EL-MISSIKAT URANIUM BEARING SILICEOUS VEINS AND THEIR ANALOGY TO EL-ERADIYA AND GATTAR GRANITES, EASTERN DESERT, EGYPT