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Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia1.90 MB
Published (Version of record)CC BY V4.0, Open Access
Published (Version of record)CC BY V4.0, Open
Journal article
Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia
Biology (Basel, Switzerland), Vol.11(11), pp.1-16
23/10/2022
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Abstract
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.
Details
- Title
- Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia
- Creators
- Jonathan Mitchell - Department of Agriculture and FisheriesTracey Scott-Holland - Department of Agriculture and FisheriesPaul Butcher - Southern Cross University
- Publication Details
- Biology (Basel, Switzerland), Vol.11(11), pp.1-16
- Publisher
- MDPI AG
- Identifiers
- 991013062311402368
- Copyright
- Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article