Flight speed and time of day heavily influence rainforest canopy wildlife counts from drone-mounted thermal camera surveys
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Whitworth, Andrew
[1
,2
,3
]
Pinto, Carolina
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Osa Conservat, Washington, DC 20005 USAOsa Conservat, Washington, DC 20005 USA
Pinto, Carolina
[1
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Ortiz, Johan
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Osa Conservat, Washington, DC 20005 USAOsa Conservat, Washington, DC 20005 USA
Ortiz, Johan
[1
]
Flatt, Eleanor
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Osa Conservat, Washington, DC 20005 USA
Univ Edinburgh, Coll Med & Vet Med, Deanery Biomed Sci, Edinburgh, Midlothian, ScotlandOsa Conservat, Washington, DC 20005 USA
Flatt, Eleanor
[1
,4
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Silman, Miles
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Wake Forest Univ, Ctr Energy Environm & Sustainabil, Dept Biol, Winston Salem, NC 27109 USAOsa Conservat, Washington, DC 20005 USA
Silman, Miles
[3
]
机构:
[1] Osa Conservat, Washington, DC 20005 USA
[2] Univ Glasgow, Coll Med Vet & Life Sci, Inst Biodivers Anim Hlth & Comparat Med, Glasgow, Lanark, Scotland
[3] Wake Forest Univ, Ctr Energy Environm & Sustainabil, Dept Biol, Winston Salem, NC 27109 USA
[4] Univ Edinburgh, Coll Med & Vet Med, Deanery Biomed Sci, Edinburgh, Midlothian, Scotland
The payload size and commercial availability of thermal infrared cameras mounted on drones has initiated a new wave in the potential for conservationists and researchers to survey, count and detect wildlife, even the most complex of habitats such as forest canopies. However, several fundamental design and methodological questions remain to be tested before standardized monitoring approaches can be broadly adopted. We test the impact of both the speed of drone flights and diel flight period on tropical rainforest canopy wildlife detections. Detection and identification rates differ between both flight speeds and diel time. Overall similar to 36% more detections were made during slower flight speeds, along with a greater ability to categorize taxonomic groups. Flights conducted at 3am resulted in similar to 67% more detections compared to flights conducted at 7am (the diel period with the lowest detection rate). However, 112% more detections could be identified to taxonomic group in 7am flights compared with 3am flights - due to the types of wildlife being identified and the assistance of the RGB camera. Although, this technology holds great promise for carrying out surveys in structurally complex and poorly known ecosystems like forest canopies, there is more to do in further methodological testing, and building automated post-processing systems. Our results suggest that drone studies in the same habitat types, with the same animal densities, could be off by multiples if flown during different times and/or at different speeds. The difference could be an alarming 5-6x variation in animal detections or identification depending on changes in these two factors alone.