The well-known dark-object subtraction method has formed one of the oldest and widely used procedures for adjusting digital remote sensing data for effects of atmospheric scattering. The method's limited capabilities, relative to more sophisticated methods, are at least partially offset by its wide applicability, due its requirement for little information beyond the image itself. This study examines alternative applications of the procedure to evaluate its effectiveness, using a SPOT HRV XS image of irregular terrain in southwestern Virginia and a sequence of Landsat MSS data depicting a region in south central Virginia. Assessment of the success of the adjustment is conducted using chromaticity co-ordinates (using the method of Alfoldi and Munday (1978)), from corrected values, and comparing corrections to the original data. A successful correction shifts chromaticity co-ordinates away from the equal radiance point towards the purer regions near edges of the diagram. Further, some categories, when corrected successfully, will occupy known positions within chromaticity space. Assessment of the modification proposed by Chavez (1988) was conducted by examining the effects of choosing alternative starting haze values, and effects of alternative choices for atmospheric models. One difficulty in applying the 1988 modification is that it appears to be difficult to make accurate assessments of atmospheric conditions.