Kernel-driven model fitting of multi-angle thermal infrared brightness temperature and its application

This paper has proved the data fitting and extrapolating ability of the kernel-driven model in TIR band by simulation of the multi-angle thermal infrared images of Linze grassland acquired in WATER campaign with the model. Additionally, the most suitable kernel-driven model available for multi-angle thermal imagery has been identified. In the feature space of land surface temperature (LST) and a combination of model coefficients which describes the actual surface directional radiative characteristics, a multi-angle thermal infrared dryness index (MTDI) is constructed and extracted out. The correlation coefficient of simulated MTDI and corresponding Temperature-Vegetation Dryness Index (TVDI) is greater than 0.87. It can be inferred that the kernel driven model is also effective in the analysis of directional radiative information in thermal infrared band.