Laser scanner and drone photogrammetry: A statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration

This work evaluated the accuracy of 3D models generated by a DJI Mavic Pro drone with 3DF Zephyr software photogrammetry. The models were compared to models generated by a Trimble X7 laser scanner. The tests were performed in the outdoor area of a vehicle parking inbound to simulate the characteristics of a crime scene. Ground control points (GCPs) were distributed in ten positions within the surroundings. In manual flight, the drone performed nadiral photographs from one side to the other side and with an elliptical 45 degrees center pointed. Three altitudes where tested: 10 m, 20 m and 40 m. The Trimble X7 laser scanner performed six scans and generated one set of point clouds. Drone photogrammetry returned eligible data for distances of 20 m and 40 m with errors of similar to 0.25 mm. To increase the overlay in the photogrammetry procedure, all photographs from distances of 10-40 m were processed, returning an error of similar to 0.53 mm. The results of the measured distances, which were manually picked from the GCPs, from the 3D-scanned model and photogrammetric 3D models were then statistically analyzed. The Trimble X7 laser scanner showed an average error of 3 cm, which was approximately equivalent to the results obtained with all images or when using a known scale value for the drone photographs, presenting no significant differences among the evaluated methods. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This study evaluated the accuracy of 3D models generated by a DJI Mavic Pro drone and a Trimble X7 laser scanner, showing that drone photogrammetry produced highly accurate data at distances of 20 m and 40 m in an outdoor area simulating a crime scene. The results were statistically analyzed and compared with the laser scanner data, with no significant differences observed in the evaluated methods.