Using satellite and airborne aerial imagery in simulation systems entails labor intensive imagery preparation. Making aerial imagery suitable for use as draped imagery in a terrain database often requires orthorectification, pan sharpening, color balancing, mosaicking, tiling, cloud removal, and shadow reduction or elimination. Ensuring correlation between the aerial imagery and vector feature data requires significant manual labor, including adding and aligning features to match the imagery, recoloring imagery pixels when a feature is not wanted, and resolving the disparities resulting from source collection differences. Moreover, if any type of material-based simulation model is required, material classification is requisite, which can be tedious even with the best automated tools. Most aircraft simulation system database builders view this labor intensive imagery preparation as unaffordable and unnecessary. But, ground-based simulation system database builders cannot dismiss these preparation steps. Aerial imagery artifacts are not easily overlooked when, in the visual system, the trainee sees “driving on tops of cars on the road�, or “walking on the tops of the trees on the ground�. When higher resolution imagery is used, the negative artifacts are more distracting. The Synthetic Environment (SE) Core program has developed a unique set of imagery processing tools and techniques to address these imagery artifacts and processing deficiencies. This paper unravels the complexities of using aerial imagery in ground-based virtual and gaming simulation systems and explores the affordability of using synthetically generated imagery alternatives and automated material classified techniques. These tools and techniques, when applied, result in highly correlated, artifact-free Controlled Image Base (CIB) imagery, full color aerial imagery, ground surface imagery, ground surface material masks, and material classified sensor maps. This paper describes how these techniques are applied, highlights the results of the improved simulation scene quality, and details the exceptional fidelity achievable in the material representations.