基于高光谱热红外发射率光谱的地表岩石CaO含量定量估计

Quantitative Estimation of CaO Content in Surface Rocks Using Hyperspectral Thermal Infrared Emissivity

通过对西藏冈底斯山东段23种岩石固体样本的野外发射率光谱测量,分别分析了这些样本的CaO含量与热红外发射率原始光谱和一阶微分光谱的相关关系。在此基础上,建立了几种典型的回归模型,并对各种建模结果进行了比较。结果表明,利用高光谱热红外发射率光谱反演地表岩石CaO的含量是可行的;地表岩石CaO含量与热红外发射率光谱特征之间有较好的对应关系;在10.3～13μm波长范围内,岩石的发射率随CaO的含量增加而降低;相比原始发射率光谱,一阶微分光谱具有更好的预测效果。结果为遥感岩矿识别提供了一种新的思路。

The objective of the present paper is to study the quantitative relationship between the CaO content and the thermal infrared emissivity spectra.The surface spectral emissivity of 23 solid rocks samples were measured in the field and the first derivative of the spectral emissivity was also calculated.Multiple linear regression（MLR）,principal component analysis（PCR） and partial least squares regression（PLSR） were modeled and the regression results were compared.The results show that there is a good relationship between CaO content and thermal emissivity spectra features;emissivities become lower when CaO content increases in the 10.3~13 mm region;the first derivative spectra have a better predictive ability compared to the original emissivity spectra.