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首先在地表比辐射率为已知的条件下，提出一个非线性迭代温度反演模型，我们对不同的地表和大气条件进行了模拟计算，结果表明当大气温度廓线误差－２Ｋ－２Ｋ，水汽廓线误差±２０％时的温度均方根误差为０．４８Ｋ。当大气模式误差一个模式时反演的温度均方根误差为０．８５Ｋ。在此基础上，引人相邻像元的概念，相邻像元的大气状况可以认为是相同的，应用两个时相的遥感影像数据，假定在两个相近时相之间地表比辐射率值不变，建立地表比辐射率与温度的反演模型。我们对不同的地表和大气条件进行了模拟计算，结果表明当大气温度廓线误差－２Ｋ－２Ｋ，水汽廓线误差±２０％时地表温度均方根误差小于１．５Ｋ，地表比辐射率均方根误差小于０．０２，地表辐射均方根误差为１％；当大气温度廓线误差－２Ｋ－２Ｋ，水汽廓线误差±１０％时，地表温度均方根误差小于１．０Ｋ，地表辐射均方根误差小于０．６％。
Firstly, a non-linear iterative temperature inversion model is proposed under the condition that the specific emissivity of the surface is known, and we simulate the different surface and atmospheric conditions. The results show that when the atmospheric temperature profile error is -2K-2K, The root mean square error of the temperature when the profile error is ± 20% is 0.48K. The root mean square error of the temperature of inversion is 0.85K when atmospheric mode error is a mode. On this basis, introducing the concept of adjacent pixels, the atmospheric conditions of adjacent pixels can be considered as the same. Applying the remote sensing image data of two phases, it is assumed that the surface emissivity The same value, the establishment of surface emissivity and temperature than the inversion model. We simulated different surface and atmospheric conditions. The results show that the mean root mean square error of surface temperature is less than 1.5 K when the air temperature profile error is -2K-2K and water vapor profile error is ± 20% The root mean square error is less than 0.02 and the root mean square error of surface radiation is 1%. When the error of atmospheric temperature profile is -2K-2K and the error of water profile is ± 10%, the root mean square error of surface temperature is less than 1.0K. The root mean square error of radiation is less than 0.6%.