Surface information extracted from satellite remote sensing has been used as input to a pollutants atmospheric dispersion model (PATM); effects in terms of turbulence parameters values and dispersion were evaluated. PATMs need 2D distributions of a set of surface biophysical parameters to model turbulence. Usually these parameters are set starting form a Land Use/Land Cover (LULC) map using predefined parameterization schemes, linking LULC categories to parameters values. Satellite remote sensing information could improve the accuracy of both LULC maps and surface parameters values, but operational methodologies are needed to routinely feed models with this information. As a contribute to this subject, we used ASTER images to update/integrate the CORINE Land Cover map and to directly calculate surface albedo, feeding the models of the Aria Industry atmospheric dispersion package with the new dataset. SPRAY has been used to simulate the dispersion of an inert generic pollutant emitted from two virtual sources on a 30 km x 40 km domain in a study area located at Venice (Northern Italy). Retrieved albedo showed mean values for each LULC category very close to the model internal values; use of the updated LULC map resulted in little changes in the mean values of the turbulence parameters, but in a different distribution of them over the domain. Particles distribution changed accordingly.