Lithological Mapping Using Different Classification Algorithms in Western Antalya, Turkey

Manap, Hatice Seval

doi:10.5593/sgem2018/2.2/s08.069

Cited by 4 publications

(2 citation statements)

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“…Emission and Reflection Radiometer (ASTER) and Sentinel 2 (S2) data were integrated to discriminate the exposed lithologies and delineate the hydrothermal alterations in zones of prospective mineralization. The former was picked out due to its prominent applications in geological explorations, while the latter was mainly selected due to its higher spatial resolution that may help detailed investigations (Yu et al, 2012;Pour and Hashim, 2014;Othman and Gloaguen, 2017;Manap and San, 2018;. ASTER is mounted on the Terra satellite platform to collect data in the visible and near-infrared, shortwave infrared, and thermal infrared regions (Table 1; Shebl et al, 2022).…”

Section: Remote Sensingmentioning

confidence: 99%

Mapping Structurally Controlled Alterations Sparked by Hydrothermal Activity in the Fatira–Abu Zawal Area, Eastern Desert, Egypt

BADAWI

ABDELATIF

Shebl

et al. 2023

Acta Geologica Sinica (Eng)

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The Eastern Desert of Egypt suffered a protracted period of deformation triggered by cratonization of the new juvenile crust known as the Arabian Nubian Shield (ANS), which has been proposed for potential gold discoveries associated with the corresponding tectonic event. The Fatira area, on the border of Egypt's Northern and Central Eastern Deserts, is covered with metavolcanic rocks twisted by a dextral relocation of the Fatira Shear Zone (FSZ) relative to the Barud magmatic body. The recent study evaluated many deformed post‐orogenic granitic intrusions and felsite dikes associated with promising mineralization localities, notably orogenic gold deposits. The combination of various field observations and remote sensing data, followed by the analysis of aeromagnetic enhanced maps, allowed the differentiation of distinct lithologies, structural features, and hydrothermal alterations in the study area. Additionally, the integrated results obtained from the different interpretation techniques are utilized to identify and confirm the previously supposed mineralized localities in the Fatira and Abu Zawal areas and predict other matched localities. The final ASTER, Sentinel 2 hydrothermal alteration, and orientation entropy heat maps demonstrate the association between these mineralized regions and major structures related to the FSZ late stage of deformation rather than other structures studied throughout the area of interest.

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Section: Remote Sensingmentioning

confidence: 99%

Mapping Structurally Controlled Alterations Sparked by Hydrothermal Activity in the Fatira–Abu Zawal Area, Eastern Desert, Egypt

BADAWI

ABDELATIF

Shebl

et al. 2023

Acta Geologica Sinica (Eng)

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“…Toward impartial lithological classifications, several Machine Learning Algorithms (MLAs) have been widely implemented [9,14,[21][22][23][24][25][26][27][28][29][30][31][32]. One of the most powerful algorithms that is mostly utilized and recommended by several studies is the support vector machine [5,9,14,29,31,[33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Impact of DEMs for Improvement Sentinel 2 Lithological Mapping Utilizing Support Vector Machine: A Case Study of Mineralized Fe-Ti-Rich Gabbroic Rocks from the South Eastern Desert of Egypt

et al. 2023

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Fused remote sensing datasets have greatly contributed to enhancing lithological targets and providing significant information for mineral exploration. For instance, multispectral datasets can discriminate rock units through their unique spectral signatures. Digital Elevation Models (DEMs) could be an effective tool boosting lithological discrimination based mainly on their topographic variations. Consequently, the current study applied the power of the support vector machine (SVM) algorithm and the integrated Phased Array L-type band Synthetic Aperture Radar (PALSAR) DEM and multispectral Sentinel 2 data to: 1—Create an updated lithological map of a poorly mapped arid terrain (Khashir-Ras El-Kharit district, Eastern Desert of Egypt), and 2—Compare and assess the distribution of ferrogabbros with the aim of improving the localization of these rock bodies and investigating their mineral content. Our results enhanced the lithological mapping and revealed a better generalization of mineralized ferrogabbros when the input was a fused DEM with Sentinel 2 compared to the salt and pepper effect observed when adopting the Sentinel 2 solely as the input data. Additionally, the current research strongly recommends detailed exploration programs for Fe-Ti oxide ores within the gabbroic rocks delineated through the resultant thematic map. The ferrogabbros were subjected to a comprehensive analysis involving whole rock geochemistry, XRD, EDX, and light-reflecting investigations, which revealed the existence of magnetite, titanomagnetite, and hematite. The titanomagnetite crystals display subhedral morphology and exhibit fine- to medium-grained surfaces with irregular shapes. X-ray diffraction (XRD) analysis revealed the presence of magnetite and hematite in the concentrated Fe-Ti oxides. Additionally, the whole rock geochemistry highlighted the origin of the ferrogabbros and their proposed tectonic setting as an alkaline to calc-alkaline magma type that developed in a continental arc setting.

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Advanced land imager superiority in lithological classification utilizing machine learning algorithms

2022

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Different types of remote sensing data are commonly used as inputs for lithological classification schemes, yet determining the best data source for each specific application is still unresolved, but critical for the best interpretations. In addition, various classifiers (i.e., artificial neural network (ANN), maximum likelihood classification (MLC), and support vector machine (SVM)) have proven their variable efficiencies in lithological mapping, yet determining which technique is preeminent is still questionable. Consequently, this study aims to test the potency of Earth observing-1 Advanced Land Imager (ALI) data with the frequently utilized Sentinel 2 (S2), ASTER, and Landsat OLI (L8) data in lithological allocation using the widely accepted ANN, MLC, and SVM, for a case study in the Um Salatit area, in the Eastern Desert of Egypt. This area has a recent geological map that is used as a reference for selecting training and testing samples required for machine learning algorithms (MLAs). The results reveal (1) ALI superiority over the most commonly used S2, ASTER, and L8; (2) SVM is much better than MLC and ANN in executing lithologic allocation; (3) S2 is strongly recommended for separating higher numbers of classes compared to ASTER, L8, and ALI. Model overfitting may negatively impact S2 results in classifying small numbers of targets; (4) we can significantly enhance the classification accuracy, to transcend 90% by blending different sensor datasets. Our new approach can help significantly in further lithologic mapping in arid regions and thus be fruitful for mineral exploration programs.

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Lithological Mapping Using Different Classification Algorithms in Western Antalya, Turkey

Cited by 4 publications

References 0 publications

Mapping Structurally Controlled Alterations Sparked by Hydrothermal Activity in the Fatira–Abu Zawal Area, Eastern Desert, Egypt

Mapping Structurally Controlled Alterations Sparked by Hydrothermal Activity in the Fatira–Abu Zawal Area, Eastern Desert, Egypt

Impact of DEMs for Improvement Sentinel 2 Lithological Mapping Utilizing Support Vector Machine: A Case Study of Mineralized Fe-Ti-Rich Gabbroic Rocks from the South Eastern Desert of Egypt

Advanced land imager superiority in lithological classification utilizing machine learning algorithms

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