ESTIMATION OF CANOPY WATER-CONTENT IN KONZA PRAIRIE GRASSLANDS USING SYNTHETIC-APERTURE RADAR MEASUREMENTS DURING FIFE

This paper presents the development of an algorithm to retrieve the ca nopy water content of natural grasslands and pasture from synthetic ap erture radar (SAR) measurements. The development of this algorithm inv olves three interrelated steps: (1) calibration of SAR data for ground topographic variations, (2) development and validation of backscatter model for grass canopies, and (3) estimation of canopy water content by inverting a backscattered model for cross-polarized ratio. The pola rimetric radar data acquired by the Jet Propulsion Laboratory AIRSAR s ystem during the 1989 First International Satellite Land Surface Clima tology Project (ISLSCP) Field Experiment (FIFE) are used for this stud y. The SAR data have been calibrated and corrected for the topographic al effects by using the digital elevation map of the study area. The b ackscattering coefficients obtained from the SAR data for each pixel a re related to the canopy and soil parameters by employing a discrete r andom media model for vegetation The model simulations indicate that b iomass variations and surface treatments (burned and unburned) of gras s canopies affect the C-band backscatter signal but does not influence the L-band signal. This model is then validated and adjusted over tra ining areas where ground measurements were collected. An inversion tec hnique is proposed to estimate the canopy water content by using the c ross-polarized and copolarized ratios of the SAR data at C band. The r esult of the inversion algorithm shows a good agreement with the grass biomass data collected during FIFE 1989 intensive field campaign.