用多角度遥感数据反演混合像元组分温度的可行性分析

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T_v、T_s,叶面积指数LAI,叶倾角分布LAD,以及单叶面比辐射率ε_v(θ)和土壤表面比辐射率ε_v(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T_v、T_s、LAI、ε_v(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 feasibility of component temperature retrieval of mixed pixel using multi-angle remote sensing information

For the traditional method of retrieved land surface temperature (LST) using multichannel thermal infrared information, it is very difficult to improve the accuracy of LST because of the high correlation among the channels, furthermore, the component temperature can not be retrieved. Based on directional law of thermal infrared radiance of non isothermal mixed pixel, the directional model of continuous vegetation has been established and the relationship between the component effective emissivities and variables has been simulated by Monte Carlo method in this paper. Results show the thermal infrared radiance of non isothermal continuous vegetation is the function of the component temperatures T_v, T_s, leaf area index (LAI), leaf angle distribution (LAD), the single leaf emissivity ε_v(θ) and soil surface emissivity ε_s(θ).The variables left to be retrieved are only T_v, T_s, LAI and T_v(0).Theoretically, if we take advantage of four data from different viewing angles, the four variables including the component temperatures would be inversed due to the low correlation among the thermal infrared information of different viewing angles. Except the data from the vertical viewing angle, the other three data used for retrieved component temperatures should be limited to a range of 30 to 50 degrees.