An empirical study of the relation between the AIRSAR's signals and land surface parameters is conducted using data collected during MACEUROPE' 91. General additive regression models are fitted to the data simulated from a calibrated microwave backscattering model. A comparison between the model predictions and field observations indicates that the regression models are good predictors to the AIRSAR's signals over the grass-covered areas. Based on the regression relationships, a soil moisture retrieval algorithm combining the Lvband multi-polarization AIRSAR data is proposed and used to create spatial soil moisture maps of the Slapton Wood catchment.