中文摘要：

地表温度和比辐射率的准确提取和反演是热红外遥感的核心问题之一.由于地表温度/比辐射率反演问题的病态性,以及地表—大气强耦合特征等诸多问题,导致目前反演精度仍有待进一步提高.通过深入挖掘大气吸收峰/谷通道处下行辐射偏移量特性,提出了一种基于大气吸收线特征的高光谱热红外温度/比辐射率反演方法,并通过最优通道选择提高了算法的效率和精度.算法一定程度上可抑制大气校正不准确引入的误差,能够有效提高低比辐射率地物的反演精度.模拟数据结果表明：针对高比辐射率地物,算法与ISSTES方法的反演精度基本一致;针对低比辐射率地物,算法最大可提高温度0.48 K和比辐射率2.1%的精度.地面实测数据结果表明：约77%的样本温度反演误差优于1K,比辐射率误差均值优于0.01.

英文摘要：

Land surface temperature and emissivity separation（ TES） is a key problem in thermal infrared（ TIR） remote sensing. However,because of the ill-posed problem and the at-ground radiance＇s coupling with atmospheric radiance,the retrieval accuracy still needs to be improved. Through exploring the offset characteristic of atmospheric downward radiance,a temperature and emissivity retrieval algorithm based on atmospheric absorption feature was proposed from hyperspectral thermal infrared data by assuming that the land surface emissivity is equal between the adjacent channels. Furthermore,an optimal selection of channels was carried out to improve the efficiency and accuracy of method. The proposed method can reduce the influence of atmospheric correction error. The simulated results showthat the accuracy is similar to the ISSTES method（ Borel,2008） for high emissivity materials. Furthermore,the proposed method can enhance the retrieval accuracy for lowemissivity materials,that is approximately temperature 0. 48 K and emissivity 2. 1%. The results from the field measured data showthat about 77% of the samples have an accuracy of LST within 1. 0 K with the mean of LSEs lower than 0. 01.