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利用多通道信息反演陆面温度的传统方法 ,由于通道间信息的高度相关使反演结果的精度难以提高 ,并且无法得到混合像元中的组分温度。文中以非同温混合像元热红外辐射方向性规律为基础 ,建立了连续植被类型非同温混合像元热红外辐射模型 ,用蒙特卡罗方法模拟分析了连续植被的组分有效比辐射率与变量的关系。结果表明 :连续植被热辐射亮度值是组分温度Tv、Ts,叶面积指数 L AI,叶倾角分布 LAD,以及单叶面比辐射率 εv( θ)和土壤表面比辐射率εv( θ)的函数。利用先验知识对变量进行分析后表明 ,6个变量中只有 Tv、Ts、LAI、εv( 0 )需要反演。由于多角度间组分辐射亮度的相关性低 ,从理论上讲只需要 4个角度的辐射亮度观测值就可以解出 4个未知量而达到反演组分温度的目的。这 4个角度数据除选择垂直方向上辐射亮度数据外 ,应在 30°～ 50°视角范围内选择另外 3个热辐射亮度数据。
The traditional method of retrieving land surface temperature from multi-channel information makes it difficult to improve the accuracy of the inversion results due to the high correlation between the channels, and the temperature of the components in the mixed pixel can not be obtained. Based on the thermal infrared radiation pattern of non-isothermal mixed pixels, a thermal infrared radiation model of continuous-vegetation-type non-isothermal mixed pixel was established. The Monte-Carlo method was used to simulate the composition of continuous vegetation. Relationship with variables. The results showed that the values of thermal radiation brightness of continuous vegetation were Tv, Ts, LAI, LAD and the ratio of single leaf surface emissivity εv (θ) and soil surface emissivity εv (θ) function. The analysis of variables using prior knowledge shows that only Tv, Ts, LAI, εv (0) of the 6 variables need to be inverted. Due to the low correlation between the brightness of component radiation at multiple angles, in theory, only four angles of radiation brightness observations can be solved for four unknowns to achieve the purpose of inversion component temperature. In addition to selecting the data for the radiance in the vertical direction, the data for the four angles should be selected for the other three radiations from 30 ° to 50 °.