With the booming development of information technology and the growing demand for
remote sensing data, unmanned aerial vehicle (UAV) remote sensing technology has …

Over the past decade, drones have become a popular tool for wildlife management and
research. Drones have shown significant value for animals that were often difficult or …

Abstract Machine learning algorithms are being increasingly used to process large volumes
of wildlife imagery data from unmanned aerial vehicles (UAVs); however, suitable algorithms …

The abundance of litter pollution in the marine environment has been increasing globally.
Remote sensing techniques are valuable tools to advance knowledge on litter abundance …

The way an animal behaves in its habitat provides insight into its ecological role. As such,
collecting robust, accurate datasets in a time-efficient manner is an ever-present pressure for …

Data on sex ratios, age classes, reproductive success and health status are key metrics to
manage populations, yet can be difficult to collect in wild cetacean populations. Long‐term …

Assessments of individual animal health alerts to early signs of population level effects in
wildlife but often rely on logistically complex wild animal captures, hindering our …

Unmanned aerial vehicles (UAVs; or drones) are an emerging tool to provide a safer,
cheaper, and quieter alternative to traditional methods of studying marine megafauna in a …

Unoccupied aerial systems (UAS) have become common tools for ecological monitoring and
management. However, UAS use has the potential to negatively affect wildlife. Both policy …

Drones are widely used for wildlife monitoring. Deep learning algorithms are key to the
success of monitoring wildlife with drones, although they face the problem of detecting small …