Unmanned aerial vehicles as a useful tool for investigating animal movements

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.

Automated and repeated aerial observations of GPS‐collared animals using UAVs and open‐source electronics

“…However, in many species it is either not feasible to tag multiple individuals within a group, or the fission–fusion dynamics of group formation mean that individuals quickly separate (Couzin, 2006). Several studies have employed unmanned aerial vehicles (UAVs) (or drones) to study collective movement in situ (Hui et al, 2021; Iwamoto et al, 2022; Torney et al, 2018; Van Andel et al, 2015); however, there are many important ecological questions that cannot be addressed through short‐term studies of this type. Tools that allow repeated observation of the same individual at multiple time points and in different environmental conditions while simultaneously observing other individuals within the group are required to investigate questions relating to leadership dynamics (Krause et al, 2000; Pettit et al, 2015), spatial aggregation of individuals within the group (Hansen et al, 2016), information sharing and cultural transfer within the group (Simons, 2004; Stewart & Harcourt, 1994; Ward et al, 2008), and individual personality (Sasaki et al, 2018).…”

Case study of detection and monitoring of wildlife by UAVs equipped with RGB camera and TIR camera

“…Basu et al ’s (2019) paper describes how the speed of galloping giraffes was measured using unmanned aerial vehicles (UAVs), when measured with sensors mounted on a drone. Iwamoto et al ’s (2022) study describes the measurement of the movement speed of wild boars, where a UAV with appropriate sensors was also used. Hu et al ’s (2020) article indicates the use of UAVs and image analysis to determine the migration directions of Tibetan antelope groups.…”

Distance sampling with vehicle-mounted cameras for the estimation of farmland bird abundance over a wide area

“…Comparison of the observer-target distances measured by RS and unmanned aerial vehicles (UAVs) is expected to be a feasible independent field test. UAVs have become an effective tool for monitoring animal populations and individual locations (Iwamoto, Nogami, Ichinose, & Takeda, 2022;Witczuk, Pagacz, Zmarz, & Cypel, 2018). Although their application to large spatial areas remains costly, this method is highly accurate because UAVs can measure animal positions from almost directly above.…”