Abstract In aerial wildlife counts, human observers often fail to detect animals. We conducted a multi-species sample-count in Tsavo National Park, Kenya, with traditional rear-seat-observers (RSOs) and an automated ‘oblique-camera-count’ (OCC) imaging system to compare estimates of 23 wildlife species derived from these two survey methods. An aerial Total Count of elephant, buffalo and giraffe, conducted a month previously, provided a further comparison. In the Tsavo Core (9560 km2), which harbours 80% of Tsavo’s elephants, the OCC system acquired 81 000 images for interpretation, of which 67 000 were obtained in parallel with RSO-counting along 3004 km of flight line. The Tsavo outer blocks (24 171 km2) were surveyed using the OCC system without RSOs to acquire a further 84 000 images. A random sample of 11 553 images were re-interpreted to derive species-specific probabilities of detection and correction factors. Using ‘Jolly II’, non-parametric and Bayesian analyses, and applying correction factors, we demonstrate that the RSOs did not detect 14% of elephants, 60% of giraffe, 48% of zebra and 66% of the large antelopes. For comparison, the Total Count observers did not detect 27% of elephant, 33% of buffalo, 57% of giraffe and 85% of carcasses. The OCC method raises the elephant population estimate to 16 681 ± 4047 (95% cl) from the 12 722 counted in the Total Count (Z = 1.917, p = .0276). These results suggest that RSO-based methods have significantly undercounted wildlife populations. To align with improved counting methods, previous results need to be re-calibrated.

中文翻译：

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在肯尼亚察沃的一次野生动物调查中将自动高清倾斜摄像系统与后座观察员进行比较：将多物种航空计数提升到一个新的水平

摘要 在空中野生动物计数中，人类观察者通常无法检测到动物。我们在肯尼亚察沃国家公园进行了多物种样本计数，使用传统的后座观察器 (RSO) 和自动“倾斜相机计数”(OCC) 成像系统来比较来自这两种调查方法。一个月前进行的大象、水牛和长颈鹿的空中总计数提供了进一步的比较。在拥有 Tsavo 80% 大象的 Tsavo Core（9560 平方公里）中，OCC 系统获取了 81 000 张图像进行解释，其中 67 000 张是与沿 3004 公里飞行线的 RSO 计数并行获得的。使用 OCC 系统在没有 RSO 的情况下对 Tsavo 外部块体（24 171 平方公里）进行了调查，以获取另外 84 000 张图像。重新解释了 11 553 张图像的随机样本，以推导出特定物种的检测概率和校正因子。使用“Jolly II”、非参数和贝叶斯分析以及应用校正因子，我们证明 RSO 没有检测到 14% 的大象、60% 的长颈鹿、48% 的斑马和 66% 的大型羚羊。相比之下，总计数观察者没有发现 27% 的大象、33% 的水牛、57% 的长颈鹿和 85% 的尸体。OCC 方法将大象种群估计值从总计数 (Z = 1.917, p = .0276) 中计数的 12 722 提高到 16 681 ± 4047 (95% cl)。这些结果表明，基于 RSO 的方法显着低估了野生动物种群。为了与改进的计数方法保持一致，需要重新校准以前的结果。