被动微波遥感反演地表温度研究进展

热红外遥感技术在地表温度反演中已经获得了丰厚的果实,反演精度可达到1 K,然而,大气中云雾和尘埃对热红外遥感探测地表温度影响很大,限制了热红外遥感反演地表温度的应用.相反,被动微波遥感受大气干扰小,可穿透云层获取地表辐射信息,并具有全天候、多极化等特点,在地表温度反演中具有独特的优越性.但是微波信号也受多种因素的影响,其反演地表温度的算法目前尚不成熟,有待进一步研究.根据不同微波辐射计特征,系统讨论并评估了被动微波反演地表温度的经验模型、物理模型以及半经验模型及其发展过程,指出目前研究的难点和缺点,为今后相关研究提供参考.

Progress in Land Surface Temperature Retrieval from Passive Microwave Remote Sensing Data

Much achievements have been presented for retrieving land surface temperature (LST) from thermal infrared satellite sensor data. The accuracy of retrieval results can reach 1K. But the thermal infrared remote sensing is greatly influenced much by cloud, atmospheric water content and rainfall, which may cause many difficulties in LST retrieval studies. However, the passive microwave remote sensing can just overcome these disadvantages. Passive microwave emission can penetrate non-precipitating clouds, thereby providing a better representation of LST under nearly all sky conditions. Passive microwave remote sensing holds a unique advantage in retrieving LST. But passive microwave emission can also be influenced by certain surface factors. So more efforts are needed for the algorithms improvement of LST retrieval from passive microwave remote sensing data at present. This paper systematically reviews the empirical LST retrieval models, physical LST retrieval models and semi-empirical LST retrieval models from passive microwave data based on different passive microwave radiometers. The weakness and difficulties for LST inversion at the present study stage are analyzed, which may be very helpful to the future researches related to the kind of microware sensors.