Drone-assisted disaster victim identification: analysis of different drone heights and camera specifications for capturing images of secondary identifiers

This is the authors' abstract. We don't add key points for this paper.

Primary identifiers, such as fingerprints, deoxyribonucleic acid (DNA), and dental comparisons, offer reliable identification for deceased victims. When such evidence is unavailable, secondary identifiers such as clothing, personal belongings, and other unique markers can also provide sufficient information. Furthermore, delays in locating and recovering dead victims may lead to decomposition, complicating identification. Technological advancements have revolutionised the role of drones in disaster operations by streamlining the Disaster Victim Identification (DVI) process. However, limited research exists on drone applications for DVI. Thus, this study explores the use of drones to capture images of secondary identifiers at various heights and lens specifications. DJI Mavic 2 Zoom (M2Z) and Matrice 300 RTK (M300) drones were deployed, and all images were assessed by forensic experts using the Secondary Identifier DVI Scoring Card (SIDSC). The M2Z drone at 5 m with a 48 mm lens and the M300 drone at 50 m with 20x zoom produced the best image quality and orientation. Both intra/inter-operator precision analyses showed no significant difference (p>0.05) when using SIDSC. Results from this study provide foundations for optimised heights and camera specifications in capturing secondary identifiers. In conclusion, drone technology enhances DVI protocols by enabling early, high-quality data collection before evidence is compromised.