
doi: 10.1111/fme.12420
AbstractIllegal fishing is a global issue that threatens the viability of fishing industries and biodiversity conservation. Management agencies typically use on‐ground surveillance to monitor and minimise illegal fishing practices, the efficacy of which may be enhanced by integrating emerging remote sensing technology. Affordable drones may contribute to cost‐effective detection of illegal fishing activity and associated gear, although their application has yet to be evaluated in many types of fisheries. Here, the utility of drones for the detection of crab traps and floats set in a shallow estuary was quantitatively tested, and the effects of survey altitudes, cameras and monitor screens on detection rates were determined. It was found that drone flight altitude and float colour influenced the detection rates of common crab trap floats, with infrared cameras improving the detection of floats camouflaged by black paint. However, the type of monitor screen used by the drone operator had no influence on the detection of crab traps. Overall, it appears drones can contribute to cost‐effective compliance in estuarine trap fisheries, and the approach can contribute to evidence‐based standard operating procedures.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
