The Simple Soil-Plant-Atmosphere Transfer - Remote Sensing (SiSPAT-RS) model was developed to simulate soil-vegetation-atmosphere energy and water transfers as well as remote sensing measurements at field scale, in the visible and thermal infrared domains. This model has been validated on the Alpilles-ReSeDA (Remote Sensing Data Assimilation) experimental database gathering micrometeorological data and remote sensing observations. Sensitivity and uncertainty studies were performed with the SVAT model and the radiative transfer models using stochastic technics like Monte Carlo's methods. The results permit us to quantify the model uncertainties linked to parameters and initial conditions uncertainties, such information which is essential to carry on assimilation studies. Here, we present the results concerning the sensitivity analysis and the results of the calibration on an experimental agricultural field of ReSeDA experiment.