Multispectral and Hyperspectral Remote Sensing: Target Area Generation for Porphyry Copper Exploration in the Namaqua Metamorphic Province, South Africa

Ngcofe, Luncedo; Minnaar, H.; Halenyane, K.; Chevallier, L.

doi:10.2113/gssajg.116.2259

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…Because the Kaolinite-bearing formation is not clearly visible (very light purple color), the ((B4/B8) * (3 + 4)/11) ratio was used to focus on showing the kaolinite index better 34 . The kaolinite pixels were clipped for the Cretaceous age formation and presented over a greyscale image for straightforward clarification (Fig.…”

Section: Methodsmentioning

confidence: 99%

Evaluation insight into Abu Zenima clay deposits as a prospective raw material source for ceramics industry: Remote Sensing and Characterization

Maged

El-Magd

Radwan

et al. 2023

Sci Rep

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The rapid development and mutations have heightened ceramic industrialization to supply the countries' requirements worldwide. Therefore, the continuous exploration for new reserves of possible ceramic-raw materials is needed to overwhelm the increased demand for ceramic industries. In this study, the suitability assessment of potential applications for Upper Cretaceous (Santonian) clay deposits at Abu Zenima area, as raw materials in ceramic industries, was extensively performed. Remote sensing data were employed to map the Kaolinite-bearing formation as well as determine the additional occurrences of clay reserves in the studied area. In this context, ten representative clayey materials from the Matulla Formation were sampled and examined for their mineralogical, geochemical, morphological, physical, thermal, and plasticity characteristics. The mineralogical and chemical compositions of starting clay materials were examined. The physicochemical surface properties of the studied clay were studied utilizing SEM–EDX and TEM. The particle-size analysis confirmed the adequate characteristics of samples for white ceramic stoneware and ceramic tiles manufacturing. The technological and suitability properties of investigated clay deposits proved the industrial appropriateness of Abu Zenima clay as a potential ceramic raw material for various ceramic products. The existence of high kaolin reserves in the studied area with reasonable quality and quantity has regional significance. It would significantly help reduce the manufacturing cost and overwhelm the high consumption rate. The ceramic manufacturers in the investigated areas are expected to bring steady producers into the industry in the long term to gain the advantage of low-cost raw materials, labor, and factory construction.

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Section: Methodsmentioning

confidence: 99%

Evaluation insight into Abu Zenima clay deposits as a prospective raw material source for ceramics industry: Remote Sensing and Characterization

Maged

El-Magd

Radwan

et al. 2023

Sci Rep

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“…Based also on geochemical indicators it is believed that the alteration assemblage at Kap Simpson could be part of a porphyry molybdenum system. Ngcofe et al (2013) mapped indicator alteration minerals for porphyry copper deposits in the Namaqua Metamorphic Province, South Africa, using HyMap imagery.…”

Section: Porphyry Copper and Molybdenum Depositsmentioning

confidence: 99%

The use of hyperspectral remote sensing for mineral exploration: a review

Bedini

2017

Jour. Hypers. Rem. Sensg.

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The hyperspectral remote sensing technology has been available to the research community for more than three decades. Since in its first steps the hyperspectral technology was also promoted as a tool for mineral exploration. Numerous mineral exploration applications of hyperspectral remote sensing have been reported. This paper provides an up-to-date and focused review of the applications of the hyperspectral remote sensing to mineral exploration. The ore deposits are grouped based on major processes of formation (magmatic, hydrothermal, sedimentary, supergene). The review shows that the hyperspectral remote sensing technology has found application to the study and exploration of a number of ore deposits including kimberlites (host-rocks of diamonds), carbonatites (host-rock of rare earth elements deposits), porphyry deposits, epithermal gold and silver deposits, skarn deposits, volcanic-hosted massive sulfide (VHMS) deposits, orogenic gold deposits, Carlin-type gold deposits, SEDEX Pb-Zn-Ag deposits. On the other hand, the possibilities of the hyperspectral technology remain still underexplored for the study and exploration of chromite deposits, Ni-sulfide deposits in mafic and ultramafic rocks, rare-metal pegmatites, greisen and related deposits, Mississippi Valley-type (MVT) Pb-Zn deposits, Kupferschiefer deposits and uranium deposits in sedimentary basins, iron ores in banded-iron formations, laterites and bauxites. A special attention has been paid in this review to the applications in mineral exploration of the emerging airborne hyperspectral thermal infrared technology. In addition, the possibilities and limitations of spaceborne hyperspectral imagery of moderate spatial resolution for detailed characterization and detection of mineralized systems are discussed for each major deposit type. The spatial resolution of the hyperspectral data is noted to be a key factor on the success of a hyperspectral exploration project. By providing a full up-to-date picture of the applications and contribution of the hyperspectral imagery to the exploration and characterization of ore deposits this review paper should be useful to the interested geological remote sensing researcher and practitioner, and to the mineral exploration manager as well.

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“…Remotely sensed Hyperspectral Imaging (HSI) data play an important role in geological investigations and mineral exploration, especially in arid and semi-arid environments [1][2][3][4][5][6]. Various hyperspectral satellites and airborne data have been used continually in geological research [5,[7][8][9]. Remote sensing techniques allow for efficient mapping and the analysis of lithological units, with such techniques becoming the preliminary steps for geological investigations thanks to the capability of providing a synoptic view of a specific Earth surface region [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Performance of Machine Learning and Deep Learning Techniques to HyMap Imagery for Lithological Mapping in a Semi-Arid Region: Case Study from Western Anti-Atlas, Morocco

et al. 2023

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Accurate lithological mapping is a crucial juncture for geological studies and mineral exploration. Hyperspectral data provide the opportunity to extract detailed information about the geology and mineralogy of the Earth’s surface. Machine learning (ML) and deep learning (DL) techniques provide an accurate and effective mapping of various types of lithologies in arid and semi-arid regions. This article discusses the use of machine learning algorithms, specifically Support Vector Machines (SVM), one-dimensional Convolutional Neural Network (1D-CNN), random forest (RF), and k-nearest neighbor (KNN), for lithological mapping in a complex area with strong hydrothermal alteration. The study evaluates the performance of the four algorithms in three different zones in the Ameln valley shear zone (AVSZ) area at eastern Kerdous inlier, Moroccan western Anti-Atlas. The results demonstrated that 1D-CNN achieved the best classification results for most lithological units. Additionally, the LK-SVM demonstrated good mapping results compared to the other SVM models, as well as RF and KNN. Our study concludes that the combination of the CNN and HyMap data can provide the most accurate lithologic mapping for the three selected region, with an overall accuracy of ~95%. However, this study highlights the challenges in identifying different lithological units using remotely sensed data due to spectrum similarities induced by similar chemical and mineralogical compositions. This study emphasizes the importance of carefully considering and evaluating ML and DL methods for lithological mapping studies, then recommends the high-resolution hyperspectral data and DL models for accurate results. The implications of this study would be fascinating to exploration geologists for Mineral Prospectivity Mapping (MPM), especially in selecting the most appropriate techniques for highly accurate mineral mapping in metallogenic provinces.

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Multispectral and Hyperspectral Remote Sensing: Target Area Generation for Porphyry Copper Exploration in the Namaqua Metamorphic Province, South Africa

Cited by 6 publications

References 30 publications

Evaluation insight into Abu Zenima clay deposits as a prospective raw material source for ceramics industry: Remote Sensing and Characterization

Evaluation insight into Abu Zenima clay deposits as a prospective raw material source for ceramics industry: Remote Sensing and Characterization

The use of hyperspectral remote sensing for mineral exploration: a review

Evaluating the Performance of Machine Learning and Deep Learning Techniques to HyMap Imagery for Lithological Mapping in a Semi-Arid Region: Case Study from Western Anti-Atlas, Morocco

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