Abstract
Population surveys of crocodilians using uncrewed aerial vehicles (UAV) or drones may become accurate and cost-effective alternatives to more traditional approaches. However, there are currently no quantitative methods for deriving body condition scores of crocodilians through remote sensing. This study presents seven UAV-based morphometric measures collected from rectified aerial imagery of farmed Nile crocodiles. Two hundred and eighty-eight Nile crocodiles, from two commercial crocodile farms in South Africa were included in this study. One farm housed crocodiles which appeared to have wider abdominal girths than those on the second farm, allowing comparisons for a range of sizes and body condition states. An initial disturbance assessment was conducted, and an appropriate flight altitude selected for image acquisition of farmed Nile crocodiles. Altitudes between 40m and 60m above ground level suited the studies requirements and minimized disturbance. A UAV-based body condition index for Nile crocodiles was then developed, offering a non-invasive alternative to traditional condition scoring methods. The body condition index (BCI) was calculated for each crocodile by measuring the relationship between total length and belly width (with the equation: BCI = BW/TL*10) derived from photogrammetrically processed orthophotos in GIS. The BCI values were then normalized to form a body condition score (BCS) with the equation: BCS = (BCI/1.27)*4 + 1. The BCS ranked crocodile body conditions from 1-5, where a score of 1 identified a crocodile that was comparatively thin or emaciated, while a score of 5 identified a crocodile that was relatively fat or obese in contrast to the other crocodiles assessed. A BCS of 3 was the most frequent across all crocodiles in the study, with few animals scoring a 1 or 5. The farm housing crocodiles with narrower abdominal girths had no BCS 5 occurrences, and the farm housing crocodiles with wider abdominal girths had no BCS 1 occurrences. This UAV-based body condition score could be applied to large wild or captive populations for a fast-paced health and welfare evaluation.
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