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- W4213149512 abstract "Abstract Determining animal abundance is crucial for assessing the effectiveness of management measures against pest animals. Meanwhile, investigating animal movements has become important for conducting abundance estimations of unmarked animals since the random encounter model (REM) was published. REM is a camera trapping method that derives animal density by using contact ratio between camera traps and targeted animals that randomly move at a certain speed in a given area. However, it requires an independent value, which is animal speed. For investigating animal speed, camera traps with video recording and GPS tagging are the commonly used tools. Unmanned aerial vehicles (UAVs) are currently used in wildlife monitoring to investigate the abundance of target species. It is evaluated as a tool that is non‐invasive and suitable for surveys in inaccessible landscapes. Considering these characteristics, we regarded a distant survey using this technology as suitable for investigating animal movements. Therefore, we proposed a method for estimating animal movements using UAVs and conducted a case study that aimed to investigate wild boars' movements. We collected 11 video samples that successfully followed the movements of wild boars from 26 UAV flights in total, and the average speed of their movements derived from all the samples was 1.54 km/24 hr. We found that issues can be improved, including species identification, video sample length, and animal behaviours or activity patterns. On the other hand, our method showed potential for applying to species with specific characteristics in their body size, shape or activity patterns. With improvements in the issues mentioned above, UAVs would become an alternative tool for investigating animal movements." @default.
- W4213149512 created "2022-02-24" @default.
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- W4213149512 date "2022-02-28" @default.
- W4213149512 modified "2023-10-16" @default.
- W4213149512 title "Unmanned aerial vehicles as a useful tool for investigating animal movements" @default.
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- W4213149512 doi "https://doi.org/10.1111/2041-210x.13829" @default.
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