Thesis: Land surface temperature retrieval from hyperspectral thermal infrared data

Land surface temperature (LST) is a key parameter in the physics processes of surface energy and water balance at regional through global scales (Anderson et al., 2008). The LST can be obtained with the satellite-based thermal infrared (TIR) data through the radiative transfer equation (RTE). Hyp erspectral TIR data with more refined spectral characteristics provide a great deal of information on land surface processes, especially LST. With a large number of channels, hyperspectral TIR can increase the stability of the equation system, and can also provide more constraints for the separation of surface temperature and emissivity that are more fit with the true physical properties of the surface, and thus can improve the retrieval accuracy of LST. Therefore, hyperspectral TIR data information is further explored with the target of providing LST information in our research.Our research adopts hyperspectral infrared data as the main source information and takes surface temperature retrieval as the research goal to carry out corresponding work with the support of the radiation transfer model and the database of atmospheric profiles and surface emissivity.