Identification Of Hydrothermal Alteration Zone For Exploring Gold Deposits Using ASTER Data

Remote sensing technique plays a very significant role in the early stage of exploration strategy,due to its high significance in Carrying out work scientifically and effectively in a short period,Useful for the evaluation of the potential mineral resources,and estimate the potential and spatial distribution of mineral resources.The main objectives of this study are to carry out regional geological mapping and gold prospecting in the north Sodari area,Northern Kordofan State,central Sudan.The selection of the study area was based on its favorable gold mineralization geological setting,identify alteration zones existence and distribution,analyze the structure of the study area and its control on alteration zones distribution,classify alteration zones distribution,and produce an accurate classified map with potential areas.Using Geographic Information System(GIS)and Remote Sensing technology,the researcher used an ASTER satellite image of North Kordofan area,after radiometric correction A package of digital image processing techniques was applied to ASTER multispectral image to increase the visual interpretability of the various lithological units for geological mapping and delineation of alteration zones,which represent possible target zones for gold mineralization.Different color composite images in addition to the result of image transformation(including color composition,Band Ratio BR,Relative Band Depth RBD,and Principal Component Analysis PCA)were prepared to facilitate the delineation of the main rock groups.Furthermore,the GEOMATICA LINE algorithm and ROCKWORK were used to extract structure lineaments and analyze study area structure features.Finally,the Maximum Likelihood supervised classification method was applied for alteration zone classification and comparing the accuracy of the PCA dataset and BR/RBD datasetsResults indicated that the integration of the image processing techniques has a great ability to obtain significant and comprehensive information for the reconnaissance stages of hydrothermal alteration zones in the study area.As well as the image processing was the discovery of many shear zones which trended NNE-SSW affecting most of the rock types.The Maximum likelihood supervised classification reveals the BR/RBD dataset has more overall accuracy percentage of 88.89% compared to the PCA dataset of 85.45 %.The study was validated by random 32 samples from favorable and un favorable areas analyzed by ALS Loughrea Laboratory the average concentrating was 0.917 ppm overall the samples.