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基于反射光谱预测哈图-包古图金矿区地球化学元素异常的可行性研究
引用本文:李慧,蔺启忠,刘庆杰,王钦军.基于反射光谱预测哈图-包古图金矿区地球化学元素异常的可行性研究[J].遥感信息,2009,0(4):43-49.
作者姓名:李慧  蔺启忠  刘庆杰  王钦军
作者单位:1. 中国科学院遥感应用研究所,北京,100101
2. 中国科学院遥感应用研究所,北京,100101;中国科学院对地观测与数字地球科学中心,北京,100101
3. 中国科学院对地观测与数字地球科学中心,北京,100101
基金项目:十一五国家国家科技支撑重点项目 
摘    要:为了探讨采用遥感手段定量估算金矿区地球化学元素异常的可行性,本文基于岩石样本的Au、S、As、Fe四种元素的含量数据,分析了它们的相关关系,发现As与Au含量的关系最为密切,因此As元素含量异常从一定程度上反应了Au的异常;基于岩石样本的反射率光谱数据,采用偏最小二乘法对上述元素进行了回归分析与预测。结果发现,Fe、As元素的回归模型的相关系数在训练建模过程中分别为0.8241、0.8063以上,而在验证建模过程中分布为0.6485、0.5472,它们均远高于S和Au元素回归模型的相应的相关系数。因此,利用岩石样本反射率光谱定量估算As元素的含量是可行的。

关 键 词:地球化学元素异常  金矿化    偏最小二乘  哈图  包古图
收稿时间:2008-10-15
修稿时间:2008-11-12

Feasibility Research on Estimating Geochemistry Element Abnormity Based on Reflectance Spectrum of Gold Deposit in Hatu-Baogutu
LI Hui,LIN Qi-zhong,LIU Qing-jie,WANG Qin-jun.Feasibility Research on Estimating Geochemistry Element Abnormity Based on Reflectance Spectrum of Gold Deposit in Hatu-Baogutu[J].Remote Sensing Information,2009,0(4):43-49.
Authors:LI Hui  LIN Qi-zhong  LIU Qing-jie  WANG Qin-jun
Affiliation:LI Hui , LIN Qi-zhong, LIU Qing-jie, WANG Qin-jun( 1.Institute of Remote Sensing Applications, Chinese Academy of Sciences , Beij ing 100101 ; 2. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100101)
Abstract:T o evaluate the possibility of quantificational estimating geochemistry element abnormity in the gold deposit using the remote sensing method, based on the Au、S、As、Fe contents for the rock samples of the study area, the author analyzed the correlativity between the four elements, and found that the contents of Au and As are the highest correlated, which indicates that the As element abnormity in the study area denoting the Au element abnormity at a certain extent. Further more, based on the reflectance of rock samples, the author modeled and predicted the As、Fe、S、Au content using the partial least squares regression method. The result is that the modeling of Fe and As element have higher precision than the S and Au element, and the correlation of the partial least squares regression model in the training process is 0.8241 and 0.8063 respectively, which in the predicting process is 0.6485 and 0.5472 respectively. Consequently, using the rock reflectance spectral to quantificational estimate the As content is feasible.
Keywords:geochemistry element abnormity  gold mineralization  As  partial least squares regression  Hatu  Baogutu
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