UAS for Public Safety Operations: A Comparison of UAS Point Clouds to Terrestrial LIDAR Point Cloud Data using a FARO Scanner

Joseph S. Cerreta, Scott S Burgess, Jeremy Coleman

Research output: Contribution to journalArticlepeer-review

Abstract

Unmanned Aircraft Systems (UAS) can be useful tools for public safety agencies during crime or vehicle accident scene investigations if it can provide value to the resource-constrained agency. The speed of data collection, while minimizing first responder risk, while sustaining an acceptable level of accuracy and precision compared to other tools is where the agency may find value. During a recent homicide investigation in Florida, a UAS provided saved 81% in law enforcement labor hours with an acceptable level of accuracy compared to traditional methods. The purpose of this research was to compare UAS to determine if there were differences in accuracy and precision compared to a FARO terrestrial laser scanner in a crime scene reconstruction scenario. UAS registered point clouds were generated in Pix4Dmapper from a DJI Mavic Pro, Mavic 2 Enterprise Dual, Inspire 1, Inspire 2, Phantom 4 Professional, Parrot Anafi, and Bebop 2 at flying heights of 82, 100, 150, 200, and 250 feet respectively in a grid, double grid, circle, and double grid + circle flight pattern and compared to a FARO terrestrial laser scanner. The UAS point cloud accuracy ( M = 33.2mm, SD = 6.4mm), compared to the FARO point cloud t (139) = 56.5, p = 0.00 was determined to be not as accurate as the 2.6mm-accurate FARO scanner point cloud; however, may still have an acceptable level of accuracy for investigators. An analysis of variance showed a flying height of 100 feet AGL yielded the most precision and accuracy combined when compared to other flying heights. The double grid + circle flight pattern had smaller RMS errors compared to the other flight patterns. There was also a significant difference by the UAS aircraft model used. The P4P had a smaller RMS error compared to the six other aircraft examined.

Original languageAmerican English
JournalDefault journal
DOIs
StatePublished - Jan 1 2020

Keywords

  • UAS
  • unmanned systems
  • point cloud
  • accident reconstruction
  • crime scene analysis
  • public safety
  • LiDAR

Disciplines

  • Aviation and Space Education
  • Criminal Procedure
  • Law Enforcement and Corrections
  • Management and Operations
  • Operational Research
  • Other Aerospace Engineering

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