Subpixel Temperature Estimation from Low Resolution Thermal Infrared Remote Sensing

The paper presents a new methodology adapted to the downscaling of low resolution IRT signals, i.e. the estimation of subpixel temperatures. The approach is based on the inversion of subpixel variables by multilinear regressions constrained by a priori temperature estimates provided by a physical land surface model. The method was developed and validated against a synthetic database built on model simulations. The precision of the methodology was analysed in terms of errors on the subpixel temperature estimations according to model and observation uncertainties. The impact of the number of observations used (i.e. the number of low resolution pixels considered) as well as the influence of the pixel heterogeneity were studied.