Documenting and mapping using three-dimensional (3D) technologies have become
essential in crime- and crash-scene investigations in recent years.
Traditionally, this has been accomplished using terrestrial laser scanners
(TLS), which often come with significant upfront costs. In contrast, Recon-3D,
launched in 2022, leverages the capabilities of Apple’s light detection and
ranging (LiDAR) sensor, available in Pro and Pro Max models since 2020. This
study aims to evaluate the relative accuracy of documenting vehicles in both
pre- and post-collision conditions using these technologies. A deviation
analysis was conducted utilizing CloudCompare software to compare point cloud
data collected from the Leica RTC360 laser scanner with that obtained from
Recon-3D for 7 vehicles in a pre- and post-impact condition for a total of n =
14 vehicles. At the 1, 2, and 3 cm deviation thresholds, the average percent of
points which fell below each threshold level for all vehicles was 66%, 91%, and
97%, respectively. Overall, the results indicate that Recon-3D delivers point
cloud data that is useful for pre- and post-collision vehicle documentation.