الفهرس 
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Abstract
The present study aims to investigate the use of spectral
signature of multispectral Landsat-8 data and Sentinel-2 in
geological investigation of mineral resources, besides
petrographic and chemical analysis as well as field verification
to investigate the occurrence of manganese deposits in Abu
Shaar El Qibli Area, Eastern Desert, Egypt
Several methods used for spectral enhancement of
multispectral images are used on both Landsat 8 (Operational
Land Imager; OLI) image and Sentinel-2 in order to detect
manganese layers in the study area.
The imagery subjected to several data enhancement techniques
before interpretations that included; principle component
analysis, band ratio and band algebra.
ENVI 5.1 and ArcGIS 10.2 packages were used for
digital/mathematical processing steps and to apply the resulted
models in the study area.
The spectral signature curve behavior for four samples of
manganese deposits had measured and examined carefully and
its relationship with the surface reflectance (SR) values of
Landsat 8 data and Sentinel-2 data, these relationship
considered the factor for determination of the sensitive
response bands for manganese interaction. Spectral signature is used to detecting the best formulas to mapping manganese
layers. Interpretations done based on observations made after
these manipulations, which gave characteristic differences for
the manganese layers.
The results confirmed by field verification and reveal a new
method of integrated image interpretation in terms of spectral
and spatial resolutions in identifying different rocks and
minerals.
The integration of those sensitive bands and the two mentioned
methods are the main objectives of the present investigation.
This should permit to create the manganese spatial distribution
map for the study area.
The measured spectral signature reflectance curve of the
manganese resampled to meet the spectral characteristics of
Landsat bands and Sentinel-2; both curves carefully examined
to determine the most significant response bands for
manganese ore.
The results illustrate LANDSAT and Sentinel-2 abilities to
provide information on defining manganese minerals, which
are valuable for mineral exploration activities and support the
role of PCA as a very effective and robust image processing
technique for that purpose.