Photogrammetry is widely used in the accident reconstruction community to extract three-dimensional information from photographs. This article extends a prior study conducted by the authors, whereby model accuracy was assessed for a technique that exploited vehicle edges and epipolar line projections to construct 3D vehicle models, by examining 3D roadway and site features. To do so, artificial images were generated using an ideal computer-generated camera within a computer-assisted drawing environment to allow for a known reference model to compare with results produced using photogrammetry. A systematic study was undertaken by modeling the curvature, elevation, and super-elevation of a roadway and associated markings, sidewalks, and buildings, either by relying on discrete points or utilizing epipolar lines. The models were assessed for accuracy, and the sensitivity of the accuracy to camera elevation was considered. Subsequently, the photogrammetric procedures were applied to actual sites, and the results were compared with 3D total station and scanner measurements. A further goal of this study was to evaluate modeling accuracy for cases in which a minimal number of sUAS images were included in the photogrammetry project. The findings of the current study corroborated the prior effort when scaled for the size of the objects modeled. It was demonstrated in this study that using photographs taken with a calibrated digital camera, and taking advantage of epipolar lines when modeling, allowed analysts to construct wireframe models of a real-world site, straight and curved edges included, that exhibited an average residual error of 4.1 cm (SD = 2.6 cm) when compared to scanned measurements, resulting in nominal dimensions of the object within 0.2% of the measured dimensions. The modeled site grades fell within ±0.4% of the measured grades.