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Comparing an automated high-definition oblique camera system to rearseat-observers in a wildlife survey in Tsavo, Kenya: Taking multi-species aerial counts to the next level

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

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Comparison of aerial counts with ground counts for large African herbivores

1. Over the past 50 years, aerial counts have been widely used in African wildlife management; however, the accuracy of the resulting estimates has rarely been questioned. The reliability of aerial counts of large African herbivores was examined by comparing the results of a series of systematic aerial sample counts with those from a series of line transect foot counts conducted in the Lupande Game Management Area in Zambia. 2. For most large herbivore species, the estimates from the aerial

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Cameras replace human observers in multi-species aerial counts in Murchison Falls, Uganda

Wildlife counts in Africa and elsewhere are often implemented using light aircraft with ‘rear-seat-observer’ (RSO) counting crews. Previous research has indicated that RSOs often fail to detect animals, and that population estimates are therefore biased. We conducted aerial wildlife surveys in Murchison Falls Protected Area, Uganda, in which we replaced RSOs with high-definition ‘oblique camera count’ (OCC) systems. The survey area comprises forests, woodlands and grasslands. Four counts were conducted in 2015–2016 using a systematic-reconnaissance-flight (SRF) strip-transect design. Camera inclination

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