Abstract
This work aims to apply spectral image processing techniques that have been used often to processhyperspectral data to analyze multispectral ASTER (Advanced Spaceborne Thermal Emission andReflection Radiometer) and Landsat 8 data for mapping uranium-bearing siliceous rocks within El-Missikat granite. These techniques succeeded effectively in recognition of the same features at El-Eradiyaand Gattar granites. Siliceous materials (siliceous sinter), as used here, is a spectral group of SiO2 mineralsincluding opal, chalcedony and cristobalite derived from hydrothermal fluids and/or the decomposition ofgranite. The spectral identification of such minerals depend mainly on the uses a hydration absorptionfeature that characterize some hydrated silica at wavelength region of 2.2- to 2.4-μm.The effectiveness of the hyperspectral analysis techniques used to compare a pixel spectrum with thespectra of known pure materials, extracted from the spectral end member selection procedures, includingminimum noise fraction (MNF), pixel purity index (PPI) and n-dimensional visualization. Among thoseof 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 hyperspectralanalysis of an ASTER and Landsat 8 dataset covering the studied areas, has successfully effective indetecting lithological units than traditional multispectral analysis procedures.Field validation and laboratory investigation were carried out to prove and support the resultsobtained from ASTER and Landsat 8 processing. These results succeeded to delineate additional sitesof siliceous materials that could be a promising areas to host the uranium mineralization.
Highlights
Uranium as a valuable metal cannot be detected directly by any remote sensor, the presence of minerals which form in association with this valuable metal can be located based on their spectral signatures
The improved spatial and spectral characteristics of multi spectral ASTER and Landsat 8 data have allowed the use of hyperspectral digital image processing techniques
Hyperspectral analysis of these data covering the study areas has resulted in significant improvement of the hydrothermal alteration mapping of these areas
Summary
Uranium as a valuable metal cannot be detected directly by any remote sensor, the presence of minerals which form in association with this valuable metal can be located based on their spectral signatures. The main target of this paper is to employ spectral image processing techniques that have been used often to process hyperspectral data to analyze multispectral ASTER and Landsat 8 data for the purpose of spectrally mapping uranium-bearing siliceous rocks within ElMissikat granite, hoping that these techniques will succeed effectively in recognition the same features at El-Eradiya and Gattar granites To achieve this goal, the nature and composition of siliceous materials that host the uranium mineralization at El-Missikat. Field observations revealed that uranium mineralization as well as high radioactivity are associated with the siliceous veins within and branching from the shear zone These types of siliceous material can be distinguished into three types, namely light-colored silica, black silica and jasperized silica. It is well known that Opal occur in a variety of species as opal-C (disordered cristobalite), opal-CT (disordered cristobalite and tridymite) and opal-A (amorphous opal) (Graetsch, 1994)
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