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    Geochemical characteristics and mapping of Reşadiye (Tokat-Türkiye) bentonite deposits using machine learning and sub-pixel mixture algorithms
    (Elsevier GmbH, 2024) Canbaz, Oktay; Karaman, Muhittin
    Reşadiye bentonite deposits, which play a significant role in Türkiye's bentonite production, are situated in Central Anatolia. Geochemical, mineralogical, and remote sensing data have been integrated to map the spatial distribution of clay minerals in the bentonite deposits and argillic areas. It is hypothesized that the bentonite samples occurred by the in-situ diagenetic alteration of rhyolite-dacite, trachyte, and andesite/basaltic andesitic composition pyroclastic rocks (ash-flow tuff). Biotite, clinoptilolite, calcite, dolomite, K-feldspar, opal-CT, quartz, and clay minerals are detected in most bentonite samples. The clay patterns determined in the bentonite samples in the X-ray diffraction (XRD) diagrams were 12.3–12.6 Å and were interpreted as being rich in Na-smectites. Mineral mapping in these deposits is essential for mining operations since the high-grade bentonite deposits can be affected by the other clay, gang, and ore minerals they contain in addition to the smectite. The sample spectra measurements matched montmorillonite and kaolin/smectite spectra. This study tests support vector machine (SVM) and artificial neural network (ANN) machine learning and MTMF subpixel algorithms in lithology and mineral mapping in Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. It combines the power of subpixel unmixing algorithms to determine the distribution of clay and high-grade bentonites in argillic areas discriminated by machine learning. The results showed that the SVM algorithm can map better than ANN for argillic areas. Additionally, the distribution of high-grade bentonite and kaolin/smectite bearing sites in the study area is discriminated by the mixture-tuned matched filtered (MTMF) spectral classification method. As a result, this study shows that remote sensing studies can be utilized for the exploration and monitoring of high-grade bentonite sites during and/or post-mining operations. © 2024 Elsevier GmbH
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    Hydrothermal alteration mapping using EO-1 Hyperion hyperspectral data in Kösedağ, Central-Eastern Anatolia (Sivas-Turkey)
    (Springer Science and Business Media Deutschland GmbH, 2021) Canbaz, Oktay; Gürsoy, Önder; Karaman, Muhittin; Çalışkan, Ayşe Betül; Gökce, Ahmet
    The Kösedağ region, is located in Central-Eastern Anatolia, contains a lot of base metals (Pb–Zn, Cu) and Au occurrences. The region is explored by numerous mining companies and MTA. In this research, hydrothermal alteration mapping by hyperspectral Hyperion satellite data was carried out to contribute to these explorations in a part of the region. Hydrothermal alteration is one of the initial steps in the exploration of such metallic occurrences. This study area was chosen to test the accuracy of the hyperspectral data results with those of field and laboratory study results. The in situ alteration map was prepared during field surveys and numerous samples analyses. These samples were investigated by microscopy and XRD examinations. The minerals which are belonging to argillic, sericitic, propylitic, and FeOx (iron oxide) hydrothermal alterations were determined. These minerals were checked and confirmed on the surfaces of altered samples by using ASD fieldspec 4 hi-res. The mixture tuned matched filtering (MTMF), which is one of the widely used spectral classification methods, was applied on the Hyperion data to determine the distributions of these alteration minerals in the study area. The results have shown that the comparison of field and laboratory studies and MTMF results coincided with an overall accuracy of over 86% and a kappa coefficient of 0.80. The alteration map has been generated using the MTMF method, has been the first hyperspectral research of the hydrothermal alteration mineralogy in the region. Consequently, the generated map can be used as a basic alteration map during exploration studies of hydrothermal base metal mineralizations in the region. © 2021, Saudi Society for Geosciences.