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Canadian Journal of Remote Sensing
Journal canadien de télédétection
Volume 48, 2022 - Issue 5: Advances in Hyperspectral Remote Sensing
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Research Articles

Quantitative Inversion Modeling Method for Grading Deerni Copper Deposits Based on Visible and Near-Infrared Hyperspectral Data

Une méthode quantitative de modélisation par inversion pour les teneurs en cuivre des gisements de Deerni, basée sur des données hyperspectrales dans le visible et le proche infrarouge

Jingli Wanga School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou221008, China;b School of Transportation Engineering, Shenyang Jianzhu University, Shenyang110819, ChinaCorrespondence[email protected]
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Jingxiang Gaoa School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou221008, ChinaView further author information
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Jiaqi Huangc College of Resources and Civil Engineering, Northeastern University, Shenyang110819, ChinaView further author information
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Qinghui Qid School of Civil Engineering, Shenyang Urban Construction University, Shenyang110167, ChinaView further author information
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Xinqi Maoe Software College, Northeastern University, Shenyang110819, ChinaView further author information
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Wang Caoc College of Resources and Civil Engineering, Northeastern University, Shenyang110819, ChinaView further author information
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Ruibo Dingc College of Resources and Civil Engineering, Northeastern University, Shenyang110819, ChinaView further author information
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Yachun Maoc College of Resources and Civil Engineering, Northeastern University, Shenyang110819, ChinaView further author information
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Pages 592-608 | Received 10 Oct 2021, Accepted 24 Mar 2022, Published online: 21 Apr 2022

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