Abstract
Advances in drone technology have given rise to much interest in the use of drone-mounted thermal imagery in wildlife monitoring. This research tested the feasibility of monitoring large mammals in an urban environment and investigated the influence of drone flight parameters and environmental conditions on their successful detection using thermal infrared (TIR) and true-colour (RGB) imagery. We conducted 18 drone flights at different altitudes on the Sunshine Coast, Queensland, Australia. Eastern grey kangaroos (Macropus giganteus) were detected from TIR (n=39) and RGB orthomosaics (n=33) using manual image interpretation. Factors that predicted the detection of kangaroos from drone images were identified using unbiased recursive partitioning. Drone-mounted imagery achieved an overall 73.2% detection success rate using TIR imagery and 67.2% using RGB imagery when compared to on-ground counts of kangaroos. We showed that the successful detection of kangaroos using TIR images was influenced by vegetation type, whereas detection using RGB images was influenced by vegetation type, time of day that the drone was deployed, and weather conditions. Kangaroo detection was highest in grasslands, and kangaroos were not successfully detected in shrublands. Drone-mounted TIR and RGB imagery are effective at detecting large mammals in urban and peri-urban environments.
Highlights
Improvements in sensor technology and an increase in the availability of unmanned aircraft systems, have led to widespread interest in their potential use in monitoring wildlife, in both terrestrial and marine ecosystems
The number of kangaroos counted from thermal infrared (TIR) orthomosaics was underestimated in 52% of flights (n = 39), while counts from RGB orthomosaics were underestimated in 72.2 % (n = 33) of flights
Our research suggests that drone flight parameters influenced the reliability of wildlife detection, due to larger ground sampling distances with higher heights
Summary
Improvements in sensor technology and an increase in the availability of unmanned aircraft systems (drones), have led to widespread interest in their potential use in monitoring wildlife, in both terrestrial and marine ecosystems. Some challenges for effective wildlife surveys using drones remain. These include: legislation, effects on animals, automated detection, when dealing with cryptic or highly mobile species, and optimal mission planning [4,5,6,7,8,9]. Recent advances in image analysis, and reductions in the price and accessibility of thermal cameras, have led to a renewed interest in drone-based TIR imaging in wildlife surveys [10,11,12,13]. Successful TIR imaging of Drones 2020, 4, 20; doi:10.3390/drones4020020 www.mdpi.com/journal/drones
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