Application of Remote sensing and GIS for Geological Mapping and prospecting for Iron ore deposits in - El- Bir Area, Northern State, Sudan

Abstract

Abstract This study was carried out in ELBir Area, Northern State, Sudan. The area bounded by longitudes 30 o 40 ′ 23.45 //_ 31 o 00 / 52.28 // E and latitudes 20 o 57 / 34.7 // - 21 o 17 / 49.5 // 'N The study aimed to conduct geological mapping in scale 1:100 000 and mineral prospecting investigations using remote sensing and Geographic Information System (GIS) technology. The geological rock units in the study area consist of high grade gneiss, ophiolite, metasediments, metavolcanics. Different Digital Image Processing were conducted to enhance the visual interpretation of the Landsat 8 OLI data. The FCC images produced by the IHS (Intensity-Hue –Saturation) fusion of the decorrelated stretched triplet bands 7, 6 and 2,color composite 7,5,2 ,sultan ratio all theses images to reduce geological mapping (detail geological map)with scale 1:100.000. Prospecting for mineral deposits was exploited using Landsat 8 OLI data ASTER data. The Landsat 8 OLI data were transformed by band ratioing and the Feature Oriented Principal Components (FOPCT) to produce Sabins and Crosta images, this two images were supervised classified and then geospatially analyzed in GIS to support the demarcation of the alteration zones – related to mineralization. The result indicate that the probable alteration zones related to mineralization existed in the study area as two set according to the shape, as linear shape is dominant and circle to half circle shape. ASTER Spectral Analysis or spectrum analysis is analysis in terms of spectrum of frequencies or related quantities such as energies Eigenvalues. ASTER mineral indices depend to band ratio to represent iron ore minerals(laterite, iron oxide, ferrous oxide, ferrous silicates( in the study area. viThe concentrations of iron mineral are high in north, south east and south west of the study area. Spectral Feature Fitting (SFF) is an absorption feature-based method for matching image spectra to reference spectra. To obtain the best results from the SFF classification for iron minerals in the study area, the SFF gives best result for iron minerals in the study area, the result of aster mineral indices and Sff is same for concentration of iron ore in the study area. Aster mineral indices show the concentration of iron in south east and southwest of the study area. The climate, topography of the study area is hard so there are few researches inAbstract This study was carried out in ELBir Area, Northern State, Sudan. The area bounded by longitudes 30 o 40 ′ 23.45 //_ 31 o 00 / 52.28 // E and latitudes 20 o 57 / 34.7 // - 21 o 17 / 49.5 // 'N The study aimed to conduct geological mapping in scale 1:100 000 and mineral prospecting investigations using remote sensing and Geographic Information System (GIS) technology. The geological rock units in the study area consist of high grade gneiss, ophiolite, metasediments, metavolcanics. Different Digital Image Processing were conducted to enhance the visual interpretation of the Landsat 8 OLI data. The FCC images produced by the IHS (Intensity-Hue –Saturation) fusion of the decorrelated stretched triplet bands 7, 6 and 2,color composite 7,5,2 ,sultan ratio all theses images to reduce geological mapping (detail geological map)with scale 1:100.000. Prospecting for mineral deposits was exploited using Landsat 8 OLI data ASTER data. The Landsat 8 OLI data were transformed by band ratioing and the Feature Oriented Principal Components (FOPCT) to produce Sabins and Crosta images, this two images were supervised classified and then geospatially analyzed in GIS to support the demarcation of the alteration zones – related to mineralization. The result indicate that the probable alteration zones related to mineralization existed in the study area as two set according to the shape, as linear shape is dominant and circle to half circle shape. ASTER Spectral Analysis or spectrum analysis is analysis in terms of spectrum of frequencies or related quantities such as energies Eigenvalues. ASTER mineral indices depend to band ratio to represent iron ore minerals(laterite, iron oxide, ferrous oxide, ferrous silicates( in the study area. viThe concentrations of iron mineral are high in north, south east and south west of the study area. Spectral Feature Fitting (SFF) is an absorption feature-based method for matching image spectra to reference spectra. To obtain the best results from the SFF classification for iron minerals in the study area, the SFF gives best result for iron minerals in the study area, the result of aster mineral indices and Sff is same for concentration of iron ore in the study area. Aster mineral indices show the concentration of iron in south east and southwest of the study area. The climate, topography of the study area is hard so there are few researches in the study area. The research recommended that the area needs more geological the study area. The research recommended that the area needs more geologicalinvestigations.