Resumen
Many public safety agencies in the US have initiated a UAS-based procedure to document and map crash scenes. In addition to significantly reducing the time taken to document evidence as well as ensuring first responder safety, UAS-based mapping reduces incident clearance time and thus the likelihood of a secondary crash occurrence. There is a wide range of cameras used on these missions, but they are predominantly captured by mid-priced drones that cost in the range of $2000 to $4000. Indiana has developed a centralized processing center at Purdue University that has processed 252 crash scenes, mapped using 29 unique cameras, from 35 public agencies over the past three years. This paper includes a detailed case study that compares measurements obtained from a traditional ground-based real-time kinematic positioning base station and UAS-based photogrammetric mapping. The case study showed that UAS derived scale errors were within 0.1 ft (3 cm) of field measurements, a generally accepted threshold for public safety use cases. Further assessment was done on the 252 scenes using ground control scale error as the evaluation metric. To date, over 85% of the measurement errors were found to be within 0.1 ft (3 cm). When substantial errors are identified by the Purdue processing center, they are flagged for further dialog with the agency. In most of the cases with larger errors, the ground control distance was incorrectly measured, which is easily correctable by returning to the scene and performing new distance control measurements.