Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China
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 ai...
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MDPI AG
2023-11-01
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| Series: | Remote Sensing |
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| author | Mingjie Xi Wanchang Zhang Jiakui Tang Huiran Gao Masoud Jafari Shalamzari |
| author_facet | Mingjie Xi Wanchang Zhang Jiakui Tang Huiran Gao Masoud Jafari Shalamzari |
| author_sort | Mingjie Xi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T01:43:50Z |
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| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T01:43:50Z |
| publishDate | 2023-11-01 |
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| series | Remote Sensing |
| spelling | doaj.art-42ef8e08462c47c3ba9257bd0c04bf072023-12-08T15:24:55ZengMDPI AGRemote Sensing2072-42922023-11-011523553210.3390/rs15235532Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, ChinaMingjie Xi0Wanchang Zhang1Jiakui Tang2Huiran Gao3Masoud Jafari Shalamzari4Development and Research Center of China Geological Survey, Beijing 100037, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaNational Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, ChinaKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaThe 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.https://www.mdpi.com/2072-4292/15/23/5532ASTERconcentration–area modelhydrothermal alterationmultifractal modellithological discriminationremote sensing |
| spellingShingle | Mingjie Xi Wanchang Zhang Jiakui Tang Huiran Gao Masoud Jafari Shalamzari Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China Remote Sensing ASTER concentration–area model hydrothermal alteration multifractal model lithological discrimination remote sensing |
| title | Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China |
| title_full | Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China |
| title_fullStr | Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China |
| title_full_unstemmed | Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China |
| title_short | Application of a Multifractal Model for Identification of Lithology and Hydrothermal Alteration in the Dasuji Porphyry Mo Deposit in Inner Mongolia, China |
| title_sort | application of a multifractal model for identification of lithology and hydrothermal alteration in the dasuji porphyry mo deposit in inner mongolia china |
| topic | ASTER concentration–area model hydrothermal alteration multifractal model lithological discrimination remote sensing |
| url | https://www.mdpi.com/2072-4292/15/23/5532 |
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