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为利用多光谱遥感数据提取蚀变异常信息,在分析蚀变矿物的先进星载热发射和反射辐射仪(advanced spaceborne thermal emission and reflection radiometer,ASTER)和影像短波近红外(visible and near IR-short wave-length IR,VNIRSWIR)谱带的特征光谱曲线的基础上,对传统的主成分分析法进行了改进,利用特征导向主成分分析法对辽宁兴城地区进行矿物蚀变信息提取,成功的对该地区内的褐铁矿(Fe3+)、绿泥石(Mg-OH基团矿物)和高岭石(Al-OH基团矿物)进行了蚀变异常信息提取.通过实践验证和研究区地质资料表明,特征导向主成分分析法能够有效地提取蚀变信息并识别研究区内主要矿物,可以为该区的成矿预测工作提供一定的依据.
In order to extract alteration anomaly information using multispectral remote sensing data and analyze the effects of advanced spaceborne thermal emission and reflection radiometer (ASTER) and visible and near IR-short wave-length IR and VNIRSWIR) spectral bands, the traditional principal component analysis (PCA) was improved. The feature-oriented principal component analysis (PCA) was used to extract mineral alteration information in Xingcheng area of Liaoning Province. The alteration anomaly information was extracted from limonite (Fe3 +), chlorite (Mg-OH group) and kaolinite (Al-OH group) in the area.According to the geological data It is indicated that the feature - oriented principal component analysis can effectively extract alteration information and identify the main minerals in the study area, which can provide some evidences for the ore - forming prediction work in this area.