RETRIEVAL OF SOIL-MOISTURE AND VEGETATION CHARACTERISTICS BY USE OF ERS-1 WIND SCATTEROMETER OVER ARID AND SEMIARID AREAS

The aim of this study is to use the information provided by the ERS-1 wind scatterometer (WSC) over land surfaces in arid and semi-arid envi ronments to infer soil moisture in the presence of vegetation. Driven by dielectric properties and surface roughness, the soil contribution is attenuated by a factor which depends on canopy characteristics (wat er content, shape, height, density) and scatterometer viewing conditio ns. To describe the influence of vegetation on the signal, a semiempir ical 'water-cloud' model (a first-order radiative transfer solution) w as used. The optical thickness (tau) and the single scattering albedo (omega) are the parameters used to quantify vegetation contribution to the measured signal. Through a simulation analysis for different soil moisture and viewing (incidence angle) conditions, we show the import ance of tau and omega on the signal partition between vegetation and s oil contributions. To quantify the effect of vegetation on the signal, we used information on the green vegetation acquired from NOAA-AVHRR, visible and near-IR data combined with WSC satellite data in a water- cloud model to extract tau and omega. The temporal evolution of the va rious contributions to the signal was then compared for different angu lar ranges. This semiempirical model was then applied within suitable angular ranges to retrieve soil moisture.