AI Summary & Key Takeaways
AI InsightThe obtained results show that, BR, PCA and Decorrelation Stretch methods applied on NVIR-SWIR bands of Landsat-8 and ASTER were clearly discriminate the ophiolite rocks at a regional scale.
📌 3 Key Takeaways
Abstract
The Remote Sensing processing analysis have become a directing and hopeful instrument for mineral investigation and lithological mapping. Mineral exploration in general and bearing chromites associated with ultrabasic and basic rocks of the ophiolite complex in particular has been successfully carried out in recent years using Remote Sensing techniques. Yazıhan-Hekimhan (Malatya) region of East Taurus mountain belt, ranks second in terms of iron mineralization in Turkey are accepted. The area is characterized by high grade iron ore deposits in use, development and exploration. Lithological mapping and chromite ore exploration of this area is challenging owing to difficult access (High Mountain 2243 m) using the traditional method of exploration. The main objective of this research is to evaluate the capacity of Landsat-8 OLI and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery to discriminate and detect the potential zone of chromites bearing mineralized in Malatya (Yazıhan). Several images processing techniques, Vegetation Mask, Band Ratio (BR), Band Ratio Color Composite (BRCC), Principal Component Analysis (PCA), Decorrelation Stretch, Minimum Noise Fraction and Supervised classification using Spectral Angle Mapper (SAM) exist in previous studies have been performed for lithological mapping. The obtained results show that, BR, PCA and Decorrelation Stretch methods applied on NVIR-SWIR bands of Landsat-8 and ASTER were clearly discriminate the ophiolite rocks at a regional scale. In Addition, SAM classification was applied on a spectral signature of differents ultrabasic and basic rocks extracted from ASTER data. The results are promising in identifying the potentials zones of chromite ore mineralization zones within the ophiolite region. Thus, the techniques used in this research are suitable to detect or identify the high-potential chromite bearing areas in the ophiolite complex rocks using Landsat-8 OLI and ASTER data.