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Mineral mapping based on independent component analysis for spaceborne hyperspectral data

机译:基于独立成分分析的星载高光谱数据矿物图

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Independent component analysis (ICA) model is proposed to extract alteration minerals using spaceborne hyperspectral data, because the result of present methods for alteration minerals identification are affected easily by the factors including excursion and variation of spectral signatures, interference of environment conditions and insufficient spectral library. In our work, the proposed method can realize extraction of alteration minerals under condition that the prior information of mineral spectra is unknown and the background model is not built. Therefore, this method is successfully applied to spaceborne Hyperion data at Qulong district of Tibet, and the application result in our work is approximately in accord with the geological map. Four kinds of minerals have been identified, which include kaolinite, chlorite, rich-aluminium sericite, and poor-aluminium sericite. And then the result that is obtained by ICA model can illuminate the validity and practicability of the proposed method and can provide some useful information and direction for the prognostication of mineral resource.
机译:提出了利用空间高光谱数据提取蚀变矿物的独立成分分析(ICA)模型,因为现有的蚀变矿物识别方法的结果容易受到光谱特征偏移和变化,环境条件的干扰以及光谱库不足等因素的影响。 。在我们的工作中,提出的方法可以在不知道矿物谱的先验信息且没有建立背景模型的情况下实现蚀变矿物的提取。因此,该方法已成功应用于西藏曲龙地区的星载Hyperion数据,在我们的工作中的应用结果与地质图基本吻合。已经鉴定出四种矿物,包括高岭石,绿泥石,富铝绢云母和贫铝绢云母。然后通过ICA模型获得的结果可以说明该方法的有效性和实用性,可以为矿产资源的预测提供一些有用的信息和指导。

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