Beyond Platform Type: How Vegetation, Sensors, and Tactics Shape Aerial Search and Rescue Outcomes

Timely detection of missing persons is critical for successful Search and Rescue (SAR) operations, especially under challenging environmental conditions. Modern SAR efforts utilize both manned helicopters and unmanned aerial systems (UAS), often equipped with electro-optical (EO) and infrared (IR) sensors, while helicopters may also employ visual observers. Despite their widespread use, limited empirical data exists on how these platforms, sensor types, and search techniques perform across varying terrain and vegetation densities.This study presents results from the SAVIOUR 2024 field experiment, conducted during a large-scale SAR exercise in Rogaland, Norway. Twelve professional SAR aircrews (six helicopters, six UAS teams) conducted 48 search sorties across sectors with low, medium, and high vegetation density, targeting 251 human subjects. Key metrics were Probability of Detection (POD) and Time-to-Detection.Both platforms achieved high detection rates (mean POD >83%), with 54% of sorties reaching 100% POD. Vegetation density was the strongest predictor of POD, with reduced performance in high-density forest (helicopters: 71.4%, UAS: 73.3%). Platform type did not significantly affect POD when controlling for vegetation. Helicopters detected targets faster, likely due to initial sweep strategies. UAS teams favored systematic detailed searches, resulting in longer detection intervals. Sensor-based searches outperformed visual-only methods, though visual-only data were limited.We propose that coordinated, vertically separated operations—helicopters at high altitude and UAS at low altitude—can enhance efficiency through concurrent coverage. These findings offer guidance for integrated SAR practices and highlight future research needs, including AI-assisted detection and performance evaluation under diverse thermal and geographical conditions.