中文摘要：

地表发射率是地表温度遥感反演中不可缺少的参数之一。常规获取地表发射率的遥感方法中，存在温度和发射率病态反演的问题；而实验室实测方法在恒定的自然条件下测定，对于遥感实用有一定的局限性。为解决上述问题，本研究利用温度和发射率相互耦合的关系，剔除温度效应的影响，提高发射率的精度，进而提高遥感反演地表温度的精度。对于不同地表物质而言，发射率和温度耦合关系又不同，本研究针对典型的城市人造地表类型之一---水泥路面，基于合理的自然状态下水泥路面发射率和温度观测实验，筛选理想大气环境下实测数据；利用最优发射率与温度分离算法取代光谱仪自带算法，提取精度较高发射率数据；分析时序水泥路面温度和发射率数据的耦合关系，建立耦合模型，并进行验证。研究结果表明：水泥路面的发射率二阶导数与温度相关性最高，相关系数为-0.9251。以发射率二阶导数为自变量的逐步回归模型为最佳关系模型，判定系数 R2达到0.886，验证结果的均方根误差RMSE为0.2921。水泥路面温度与其发射率耦合关系模型的建立为提高遥感反演地表温度的精度提供了一种途径。

英文摘要：

Land surface emissivity （LSE） has already been recognized as a crucial parameter for the determina-tion of land surface temperature （LST） .There is an ill-posed problem for the retrieval of LST and LSE .And laboratory-based emissivity is measured in natural constant conditions ,which is limited in the application in thermal remote sensing .To solve the above problems ,the coupling of LST and LSE is explored to eliminate temperature effects and improve the accuracy of LES .And then ,the estimation accuracy of LST from passive remote sensing images will be improved .For different land surface materials ,the coupling of land surface em-issivity and land surface temperature is various .This paper focuses on studying concrete surface that is one of the typical man-made materials in urban .First the experiments of measuring concrete surface emissivity and concrete surface temperature in natural conditions are arranged reasonably and the suitable data are selected un-der ideal atmosphere conductions .Then to improve the determination accuracy of concrete surface emissivity , the algorithm worked on the computer of Fourier Transform Infrared Spectroradiometer （FTIR） has been im-proved by the most adapted temperature and emissivity separation algorithm .Finally the coupling of concrete surface temperature and concrete surface emissivity is analyzed and the coupling model of concrete surface tem-perature and concrete surface emissivity is established .The results show that there is a highest correlation co-efficient between the second derivative of emissivity spectra and concrete surface temperature ,and the correla-tion coefficient is -0.925 1 .The best coupling model is the stepwise regression model ,whose determination coefficient （R2 ） is 0.886 . The determination coefficient （R2 ） is 0.905 and the root mean squares error （RMSE） is 0.292 1 in the validation of the model .The coupling model of concrete surface temperature and concrete surface emissivity under natural conditions provides a new app