Off-road autonomy development is increasingly leveraging simulation for its ability to rapidly test and train new algorithms as well as simulate a wide variety of terrains and environmental conditions. Unstructured off-road environments require modeling complex environmental phenomena, such as LIDAR responses from vegetation. Neya has developed an approach to characterize the variability of measurements of vegetation and approximate the variability of vegetation measurements using that characterization. This method adds a small overhead to existing LIDAR models, works with many types of LIDAR sensor models, and simply requires objects to be tagged in the environment as vegetation for the sensor models to respond appropriately.