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

Abstract

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.