Short-Wavelength Infrared Spectral Analysis and 3D Vector Modeling for Deep Exploration in the Weilasituo Magmatic–Hydrothermal Li–Sn Polymetallic Deposit, Inner Mongolia, NE China

Zuo, Ling; Wang, Gongwen; Carranza, Emmanuel John M.; Zhai, Degao; Pang, Zhenshan; Cao, Kejiang; Mou, Nini; Huang, Leilei

doi:10.1007/s11053-022-10111-1

Cited by 6 publications

(1 citation statement)

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“…They distinguish between hydrothermally altered and unaltered rocks in the visible and near-infrared (0.3-2.5 µm) bands [12,13]. As a result, spectral characteristics have been widely used to pinpoint hydrothermal alteration zones using both spaceborne and aerial images for decades (e.g., [3,[14][15][16][17][18][19]). Since the 1970s, various approaches for distinguishing hydrothermal alteration zones based on the spectral properties of minerals or rocks have been proposed, such as Principal Component Analysis (PCA) [1,20], Band Ratio (BR) [20], Spectral Angle Mapper (SAM) [2,6] and Constrained Energy Minimization (CEM) [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China

Xi,

Zhang,

Tang

et al. 2023

Remote Sensing

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The Dasuji giant porphyry molybdenum deposit is one of the largest ore deposits recently discovered along the Yinshan–Yanshan–Liaoning molybdenum belt in China. Using this deposit along the Yinshan–Yanshan–Liaoning molybdenum belt as the study area, the present study proposed a two-stage approach aimed at marking out the hydrothermally altered anomalies in the study area for the guidance of future prospecting in other regions. First of all, the Principal Component Analysis (PCA) and specific Band Ratio methods were applied to the ASTER images from different acquisition dates to extract ferric oxides and hydroxyl alterations related to the porphyry molybdenum deposit. Then, the Fractal-Aided Anomaly-Overlaying Selection model was adopted to recognize two ferric and hydroxyl alteration layers for separating anomalies from the interferences caused by geology and random noise from the data. Furthermore, for lithological differentiation in the previously marked off area, the Random Forest Classifier (RFC) was applied to the composite data obtained via the ASTER, ETM, and DEM, and it is demonstrated that the DEM can significantly improve lithological mapping in areas with complex vegetation cover and topography. Based on field verification and comparison with geological maps, the research revealed that the suggested two-stage approach may effectively reduce erroneously recognized anomalies produced during the first stage while retaining ore-related anomalies for gigantic porphyry molybdenum deposit prospecting in the Dasuji area, which showed the good application potential of the proposed model to extract actual hydrothermally altered anomalies adopted for lithological discrimination and mapping.

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