煤田土壤热红外发射率特征及其有机质估算模型

利用傅立叶热红外光谱仪探测煤田土壤的光谱数据和土壤有机质含量数据,分析了原始光谱发射率的特征,求算原始发射率的一阶、二阶导数,分别建立原始发射率、一阶导数、二阶导数与有机质之间的模型,检验和评价了每个模型的适用性。结果表明：(1)土壤的有机质含量随着地表地物类型和周边环境的不同而存在明显差异；(2)无论有机质含量存在多大的差异,热红外光谱发射率随波长的增加的而变化的趋势不变；但土壤热红外光谱的发射率在8-11.5 um范围内最敏感,有机质含量的大小会对其敏感性产生影响；(3)一阶导数、二阶导数的发射率与有机质的相关性明显优于原始发射率数据,发射率数据的导数处理能够有效的增强与有机质之间的相关性,且在该研究区发射率数据的二阶导数与有机质含量相关性最高；(4)一阶导数和二阶导数的热红外光谱发射率与有机质含量之间的拟合函数效果均较为良好,尤其二阶导数发射率的指数函数效果最佳；一阶导数的多元逐步回归拟合模型预测能力略优于线性函数模型。

Soil thermal infrared emissivity characteristics and organic matter estimation models in arid region

In this paper, Fourier thermal infrared spectrograph was used to detect the soil spectroscopic data and organic content in arid region. Analyzing the characteristics of the original spectral emissivity, we obtained the first and second derivative of the original emissivity, built the models between organic matter and the original emissivity, the first derivative, second derivative respectively. The applicability of the models were examined and evaluated. The results showed that: (1) the soil organic content differed apparently, because of the different surface feature types and surroundings. (2) The change trend of thermal infrared spectral emissivity with the increase of the wavelength stayed the same. Soil thermal infrared spectral emissivity within 8-11.5 um was most sensitive to the organic content. (3) The emissivity of the first and second derivative was superior to the original emissivity apparently. Differentiating of emissivity can effectively enhance the correlation with organic matter and the second derivative of emissivity had the highest correlation with organic matter in the study area. (4) The fitting functions of organic content with the first and second derivative of the thermal infrared spectral emissivity fitted well, especially the second derivative. The multivariate stepwise regression fitting model of the first derivative had slightly stronger predictive ability than linear function model.