SOIL-MOISTURE ESTIMATION OVER GRASS-COVERED AREAS USING AIRSAR

An empirical study of the relation between the AIRSAR's signals and land surface parameters is conducted using data collected during MAC-EUROPE'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 L-band multi-polarization AIRSAR data is proposed and used to create spatial soil moisture maps of the Slapton Wood catchment.