Mitchell Jonathan D, Scott-Holland Tracey B, Butcher Paul A
Queensland Government, Department of Agriculture and Fisheries, Animal Science, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia.
Queensland Government, Department of Agriculture and Fisheries, Fisheries Queensland, 41 George Street, Brisbane, QLD 4000, Australia.
Biology (Basel). 2022 Oct 23;11(11):1552. doi: 10.3390/biology11111552.
Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020−2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks.
无人机能够实时监测鲨鱼，在对海洋生物影响最小的情况下提高海洋使用者的安全性。然而，无人机在昆士兰海滩探测鲨鱼（尤其是潜在危险鲨鱼，即大白鲨、虎鲨、牛鲨）的有效性尚未经过测试。为了确定有效性，有必要了解环境和操作因素如何影响无人机探测鲨鱼的能力。为了评估这一点，我们利用了昆士兰鲨鱼智能无人机试验的数据，该试验于2020 - 2021年在昆士兰东南部的五个海滩进行了为期12个月的操作。该试验进行了3369次飞行，覆盖1348公里，发现了174条鲨鱼（其中48条长度超过2米）。其中，探测到8条牛鲨和1条大白鲨，导致4次海滩疏散。所有海滩的平均鲨鱼发现率为3%，北斯特拉德布罗克岛（NSI）的发现率最高（17.9%），库伦姆北部最低（0%）。无人机飞行员能够区分包括大白鲨、牛鲨和长尾鲨在内的主要鲨鱼种类，并估计鲨鱼的总长度。统计分析表明，位置、其他动物的出现、季节和飞行次数（代表一天中的时间）会影响发现鲨鱼的概率。
