层状硅酸盐是火星表面含水矿物的主要存在形式之一, 也是比较火星不同沉积物和水蚀作用程度的指示矿物, 因此构建其识别模型对研究火星的地质演化极其重要。 短波红外和热红外谱段对矿物的基团、 离子光谱响应机理不同, 具有不同的识别优势, 然而国内外联合两者识别层状硅酸盐矿物则鲜有研究。 基于USGS光谱库数据, 面向火星探测器紧凑型侦查成像光谱仪(CRISM)和热辐射成像系统(THEMIS), 在层状硅酸盐的光谱响应机理研究基础之上, 分别构建短波红外识别模型与热红外模型, 进而结合短波红外和热红外谱段, 基于Fisher判别分析构建层状硅酸盐的综合识别模型。 交叉验证表明, 综合模型识别精度优于短波红外模型和热红外模型, 对90.6%的矿物样本正确识别, 有效提高了层状硅酸盐的识别精度。

Phyllosilicate belongs to hydrated silica, which is a principal form of hydrous minerals on the martian surface. It’s also an indicator in comparing different sediments and degree of aqueous alteration. Therefore, it’s essential to establish its recognition model for studying the geologic evolution of the Mars. Short-wave infrared (SWIR) spectral bands and thermal infrared (TIR) spectral bands have distinct spectral response to the mineral groups and ions, so they have distinctive advantages in detecting minerals. However the method of combining SWIR and TIR to recognize phyllosilicate is rarely studied. Based on the USGS spectral library, facing Compact Reconnaissance Imaging Spectrometer for Mars(CRISM) and Thermal Emission Imaging System(THEMIS),we conducted the research on the mechanism 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 with Fisher discriminant analysis. The results of cross validation show that the identification accuracy of combined model is the highest, which can correctly classify 90.6% of the mineral samples and improve the identification precision of phyllosilicate effectively.