Aerial surveying is a key tool for effective wildlife management. However, the high costs associated with large scale surveys means that this tool is often underutilized. We believe that computer vision can be used to dramatically decrease the costs associated with surveying, while at the same time improving the consistency of results. We present the Aerial Elephant Dataset, a challenging dataset to enable research on game detection under real-world conditions. The dataset consists of 2 074 images containing a total of 15 581 African bush elephants in their natural habitats, imaged with a consistent methodology over a range of background types, resolutions and times-of-day.