Simulated imagery has been and will continue to be a great resource to the remote sensing community. It not only fills
in the gaps when real imagery is not available, but allows the user to know and control every aspect of the scene. Over
the last 20 years we have seen its value in algorithm development, systems level design trade studies and
phenomenology investigation. The realism of this data is often linked to its radiometric accuracy. The Rochester
Institute of Technology's Digital Imaging and Remote Sensing (DIRS) Laboratory has done extensive work on making
simulations more realistic for years, while developing our in house image generator, DIRSIG. In the past we have
invested hundreds of man-hours to painstakingly build large scale scenes of real locations with manual methods.
Recently, new procedural tools and open source geometry repositories have allowed the creation of similar scenes with
improved scene clutter in significantly less time. It is now possible to assemble and build large city-scale scene
geometries with a more automated workflow over the course of a few hours. Even with these advances, an observer
viewing these high resolution, complex, spectrally and spatially textured simulated images is still visually aware that
they are nothing but simulations, albeit radiometrically and spectrally accurate. This paper will investigate the above
concern regarding simulated imagery by looking at the utility, evolution and future of image simulations.