This study outlines a method for the estimation of regional patterns of surface moisture availability (M0) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitutes a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M0 into hydrologic and atmospheric prediction models.
Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M0 is derived and is probably good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, “universal triangle,” is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M0 in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.