State-of-the-art Command, Control, Computers, Communications, Intelligence, Surveillance and Reconnaissance (C4ISR) requires affordable and timely generation of imagery to enable training that responds to requirements of the future flight. This capability needs to render realistic visible and infrared (IR) representations, in real-time, accurately mimicking real sensor capabilities and limitations, and generate plausible run-time, views that accurately simulate the intel sensor models used for analysis during mission training scenarios. Accomplishing this requires both synthetic terrain and material mapped data plus the ability to alter that data to develop new, what-if scenarios. This work describes a synthetic terrain generation and runtime process which can rapidly create many, variable, realistic, sensorenabled environments tailored to specific training objectives of operators and analysts. We mimic a physics-based sensors model to accurately simulate the data and environments intelligence officers will use to analyze and exploit synthetic imagery in real-time. This simulation process allows for more robust training than only reviewing prerecorded past scenarios. We describe our work to demonstrate the feasibility of creating plausible visible and IR “artifact freeâ€� temporal energy maps using procedurally generated techniques. We pre-bake visible and IR lighting, and simulate the sensor in real-time using a commercial-off-the-shelf game engine (Unreal4). This capability allows production of such maps to be performed without the need for fly-over imagery. This allows for better training and mission planning since trainees train on simulated situations instead of merely watching prerecorded videos.