Remote Sensing, Petrological and Geochemical Data for Lithological Mapping in Wadi Kid, Southeast Sinai, Egypt

Fahmy, Wael; El-Desoky, Hatem M.; Elyaseer, Mahmoud H.; Ayonta Kenne, Patrick; Shirazi, Aref; Hezarkhani, Ardeshir; Shirazy, Adel; El-Awny, Hamada; Abdel-Rahman, Ahmed M.; Khalil, Ahmed E.; Eraky, Ahmed; Pour, Amin Beiranvand

doi:10.3390/min13091160

Cited by 2 publications

(1 citation statement)

References 90 publications

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“…Image information formed by the red (R), green (G), and blue (B) bands can provide rich feature information. Techniques such as Principal Component Analysis (PCA), band ratio, and false-color synthesis can be employed, even in multispectral remote sensing imagery, to enhance the discrimination of different rock units [8]. Traditionally, data collection in these areas involves using total stations or Global Navigation Satellite Systems (GNSS-RTK) to create three-dimensional models, yielding detailed images of the mining zones.…”

Section: Introductionmentioning

confidence: 99%

Open-Pit Granite Mining Area Extraction Using UAV Aerial Images and the Novel GIPNet

Meng,

Zhang,

Dong

et al. 2024

Remote Sensing

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The ability to rapidly and accurately delineate open-pit granite mining areas is pivotal for effective production planning and environmental impact assessment. Over the years, advancements in remote sensing techniques, including the utilization of satellite imagery, LiDAR technology and unmanned aerial vehicles, have revolutionized the way mining areas are monitored and managed. Simultaneously, in the context of the open-pit mining area extraction task, deep learning-based automatic recognition is gradually replacing manual visual interpretation. Leveraging the potential of unmanned aerial vehicles (UAVs) for real-time, low-risk remote sensing, this study employs UAV-derived orthophotos for mining area extraction. Central to the proposed approach is the novel Gather–Injection–Perception (GIP) module, designed to overcome the information loss typically associated with conventional feature pyramid modules during feature fusion. The GIP module effectively enriches semantic features, addressing a crucial information limitation in existing methodologies. Furthermore, the network introduces the Boundary Perception (BP) module, uniquely tailored to tackle the challenges of blurred boundaries and imprecise localization in mining areas. This module capitalizes on attention mechanisms to accentuate critical high-frequency boundary details in the feature map and synergistically utilizes both high- and low-dimensional feature map data for deep supervised learning. The suggested method demonstrates its superiority in a series of comparative experiments on a specially assembled dataset of research area images. The results are compelling, with the proposed approach achieving 90.67% precision, 92.00% recall, 91.33% F1-score, and 84.04% IoU. These figures not only underscore the effectiveness of suggested model in enhancing the extraction of open-pit granite mining areas but also provides a new idea for the subsequent application of UAV data in the mining scene.

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Section: Introductionmentioning

confidence: 99%

Open-Pit Granite Mining Area Extraction Using UAV Aerial Images and the Novel GIPNet

Meng,

Zhang,

Dong

et al. 2024

Remote Sensing

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Evaluation of alteration in the geothermal province west of Cappadocia, Türkiye: Mineralogical, petrographical, geochemical, and remote sensing data

Bilgilioglu

2024

Open Geosciences

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This study determines the mineralogical, petrographical, and geochemical properties of the rocks outcropping in geothermal areas west of the Cappadocia geothermal region. These areas include Ziga, Narlıgöl, Belisırma, Ilısu, and Sivrihisar. The study reveals their hydrothermal alteration characteristics. Also, the study aims to determine the zones of hydrothermal alterations using remote sensing. Rock samples from geothermal areas were performed using optical microscopy, X-ray diffraction (XRD), scanning electron microscopy, X-ray fluorescence spectroscopy, and inductively coupled plasma–mass spectrometry techniques for the determination of mineralogical assemblages and major, trace and REE's analyses. Rock samples, determined as ignimbrites and tuff, exhibit intensive alterations. XRD analysis determined the association of alteration minerals. The dominant clay minerals were kaolinite, montmorillonite, and illite. The analyses and mineral associations are compatible with argillic, mid-argillic alteration, and silicification zones. Alteration zones were identified by classifying the ASTER satellite images of kaolinite, illite, and montmorillonite using the CROSTA technique. The alteration zones observed in this study are close to existing geothermal areas. In addition, different regions with these alterations have been identified within the study area and are expected to be a valuable reference for future geothermal exploration.

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Remote Sensing, Petrological and Geochemical Data for Lithological Mapping in Wadi Kid, Southeast Sinai, Egypt

Cited by 2 publications

References 90 publications

Open-Pit Granite Mining Area Extraction Using UAV Aerial Images and the Novel GIPNet

Open-Pit Granite Mining Area Extraction Using UAV Aerial Images and the Novel GIPNet

Evaluation of alteration in the geothermal province west of Cappadocia, Türkiye: Mineralogical, petrographical, geochemical, and remote sensing data

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