HIGHER RESOLUTION EARTH SURFACE-FEATURES FROM REPEAT MODERATE RESOLUTION SATELLITE IMAGERY

This paper demonstrates that a high-resolution reflectivity model used in conjunction with an instrument point-spread function (PSF) can bot h determine georegistration parameters of coarse resolution sensors an d improve the spatial resolution by compositing noncoincident repeat s atellite data, To demonstrate this ability, an ideal location is selec ted and several first principle assumptions are made to simplify the r eflectivity model, Twenty-three l-km advanced very high-resolution rad iometer (AVHRR) images are composited by using a Bayesian statistical sampling technique to yield estimates of a simple terrain-based reflec tivity model with 180-m resolution, The terrain values are determined from a 90-m resolution digital elevation model (DEM). The Bayesian tec hnique uses the AVHRR data to iteratively determine the most likely va lues for the model spectral albedos contained within an AVHRR field of view, Model predicted radiances far the repeat AVHRR footprints are c omputed by integrating: model albedo values over the AVHRR PSF, As a f irst-order verification, simulated AVHRR reflectivities are shown to r econstruct well a smoothly varying prescribed albedo held, Comparisons of the composited real AVHRR image result with Landsat Multi Spectral Scanner (MSS) data show that the model reconstruction resolves surfac e features, which are not resolved in a single AVHRR image.