Exploration
Hamid Geranian; Mohammad Amir Alimi
Abstract
This study employs Sentinel-2 satellite images along with the random forest algorithm to create a regional geological map. For this purpose, the independent variables consist of the images for 10 Sentinel-2 bands of the Khosuf-I region, while the class labels consist of a geological map of Khosuf-I divided ...
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This study employs Sentinel-2 satellite images along with the random forest algorithm to create a regional geological map. For this purpose, the independent variables consist of the images for 10 Sentinel-2 bands of the Khosuf-I region, while the class labels consist of a geological map of Khosuf-I divided into three and fifteen rock units. The classification accuracy of the resulting model is 90.97 and 84.85% for the three-class training and testing data, and 94.76 and 63.92% for the fifteen-class training and testing data, respectively. These models are then applied to the Sentinel-2 satellite images' data of the Birjand-IV region to prepare two preliminary geological maps. The Birjand-IV region's three-class geology map reveals that igneous rocks are present in the northern and southern regions, while sedimentary rocks occupy the middle section and metamorphic rocks are found within the region's igneous masses. Similarly, the fifteen-class geology map of Birjand-IV indicates that andesite, dacite, intermediate tuff rock units, and metamorphic rocks characterize the northern region. Conversely, the southern part of the region is mainly composed of ophiolite, flysch sediments, basaltic and ultra-basic volcanic rocks, and limestone and shale interlayers. Field studies in three areas confirm the accuracy of the preliminary geology maps.
Exploration
Ahmed Ali Madani
Abstract
Innovation in mineral exploration occurs either in the construction of new ore deposit models or the development of new techniques used to locate the ore deposits. Band ratio is the image processing technique developed for mineral exploration. The present study presents a new approach used to evaluate ...
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Innovation in mineral exploration occurs either in the construction of new ore deposit models or the development of new techniques used to locate the ore deposits. Band ratio is the image processing technique developed for mineral exploration. The present study presents a new approach used to evaluate the band ratio technique for discrimination and prediction of the Iron-Titanium mineralization exposed in the Khamal area, Western Saudi Arabia using the ensemble Random Forest model (RF) and SPOT-5 satellite data. SPOT-5 band ratio images are prepared and used as the explanatory variables. The target variable is prepared in which (70%) of the target locations are used for training and the rest are for validation. A confusion matrix and the precision-recall curves are constructed to evaluate the RF model performance and the Receiver Operating Characteristics curves (ROC) are used to rank the band ratio images. Results revealed that the 3/1, 2/1 & 3/2 band ratio images show excellent discrimination with AUC values of 0.986, 0.980 & 0.919 respectively. The present study successfully selects the 3/1 band ratio image as the best classifier and presents a new Fe-Ti mineralization image map. The present study proved the usefulness of the Random Forest classifier for the prediction of the Fe-Ti mineralization with an accuracy of 97%.
