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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. |