结合SWIR和TIR光谱特征识别火星表面层状硅酸盐

Xia Zhang, Xing Wu, Honglei Lin
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引用次数: 0

摘要

页硅酸盐是火星表面含水矿物的主要形式。它也是比较不同沉积物和水蚀变程度的指示矿物。短波红外(SWIR)和热红外(TIR)光谱带对矿物基团和离子有明显的光谱响应。然而,结合SWIR和TIR识别层状硅酸盐的研究很少。基于美国地质调查局(USGS)的光谱库,面向火星传感器:火星紧凑型侦察成像光谱仪(CRISM)和热发射成像系统(THEMIS),研究了层状硅酸盐的光谱响应机理,分别建立了SWIR和TIR识别模型,然后结合SWIR和TIR光谱特征,通过Fisher判别分析建立了层状硅酸盐的组合识别模型。结果表明,该组合模型的识别精度最高,可对90.6%的矿物样品进行正确分类,有效提高了层状硅酸盐的识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining SWIR and TIR spectral features for regnizaion of phyllosilicate of martian surface
Phyllosilicate is a principal form of hydrous minerals on the martian surface. It's also an indicative mineral in comparing different sediments and degree of aqueous alteration. Shortwave infrared (SWIR) and thermal infrared (TIR) spectral bands have distinct spectral response to the mineral groups and ions. However, combining SWIR and TIR to recognize phyllosilicate has been rarely studied. Based on the USGS spectral library, facing sensors of Mars: Compact Reconnaissance Imaging Spectrometer for Mars(CRISM) and Thermal Emission Imaging System(THEMIS), we conducted the research on the mechanis m of the spectral response of phyllosilicate, and established the SWIR and TIR identification model respectively, then combined the SWIR and TIR spectral features to build the combined recognition model of phyllosilicate by Fisher discriminant analysis. The results show that the identification accuracy of the combined model is the highest, which can correctly classify 90.6% of the mineral samples and improve the identification accuracy of phyllosilicate effectively.
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