基于热红外辐射特征的土壤水分含量估算模型研究

摘要

利用便携式傅里叶变换红外光谱辐射仪(102F),通过室内条件下对不同含水量的土壤样本进行发射率光谱测量,阐释土壤水分含量的热红外辐射特征,通过对获取的发射率光谱数据进行微分、差分以及标准比值化变换,建立基于热红外辐射特征的土壤水分含量估算模型.结果表明,在8.0～9.5 μm波段随土壤含水量的增加,土壤热红外发射率不同程度地增加,而且发射率光谱曲线在8.0 ～9.5μm波段变得平直,reststrahlen吸收特征相对减弱；在11.0～14.0 μm波段随土壤含水量的增加,土壤热红外发射率不同程度地减小,而且在12.7 μm附近存在一个吸收谷,其吸收的深度大致随土壤水分的增加而增加.通过对发射率光谱数据的微分、差分以及标准化比值处理变换,运用统计单相关分析方法确定了诊断土壤水分含量的敏感波段为8.237 μ.μm,对敏感范围8.194 ～8.279 μm输出均值进行标准化比值处理作为自变量,提出水分诊断指数的概念,建立了土壤水分含量和水分诊断指数的对数统计模型.%With the portable Fourier Transform Infrared Spectroscopy (FTIR) , the reflectance spectra of soil samples with different moisture content are measured in laboratory for expounding the characteristic of radiation in the thermal infrared part of the spectrum with different soil moisture content. A model of estimating the moisture content in soil is attempted to make based on Moisture Diagnostic Index (MDI). The dissertation concentrates on the following aspects: in general, the spectral characteristic of soil emissivity in laboratory includes the following aspects. First, in the region of 8.0 -9. 5 μm, along with the increase of soil moisture content, the emissivity of soil increases to varying degrees. The spectral curves are parallel relatively, and have a tendency to become horizontal and the absorbed characteristic of reststrahlen is also weakened relatively with the increase of soil moisture in this region. Secondly, in the region of 11.0 -14.0 μm, the emissivity of soil has a tendency of increasing. There is an absorption value near about 12. 7 μm. As the soil moisture content increases, the depth of absorption also increases. This phenomenon may be caused by soil moisture absorption. Methods as derivative, difference and standardized ratio transformation may weaken the background noise effectively to the spectrum data. Especially using the ratio of the emissivity to the average of 8 - 14 μm may obviously enhance the correlation between soil moisture and soil emissivity. According to the result of correlation analysis, the 8. 237 μm is regarded as the best detecting band for soil moisture content. Moreover, based on the Moisture Diagnostic Index (MDI) in the 8. 194 -8.279 μm,, the logarithmic model of estimating soil moisture is made.