Cleveland Bay is one of the dugong hotspots in the Great Barrier Reef region, being periodically affected by cyclones and floods that impact the seagrass beds essential to dugongs. Assessing the health of this dugong population is crucial for establishing a baseline to inform management and conservation strategies. Drones provide a cost-effective, non-invasive tool for local-scale dugong detection and high-quality imaging. We propose that drone imagery can be analysed to obtain reliable dugong body measurements through photogrammetry methods. In turn, these measurements can be used to estimate body condition as an indicator of nutritional health.
Our study aims to develop a methodology for collecting aerial imagery suitable for dugong body condition (BC) assessment and to investigate the BC seasonal variation in Cleveland Bay over one year. DJI multirotor drones are operated from boats to conduct aerial searches and record 4K videos of encountered dugongs. Suitable image frames are extracted from the videos, and a quality scoring system is applied to select the best images for analysis. During our ongoing surveys, dugong behaviour and environmental factors have posed challenges to data collection. We present our methodology, discuss its effectiveness, and provide initial insights into dugong body condition in Cleveland bay.