  The proliferation of relatively affordable off-the-shelf drones offers great
opportunities for wildlife monitoring and conservation. Similarly the recent
reduction in cost of thermal infrared cameras also offers new promise in this
field, as they have the advantage over conventional RGB cameras of being able
to distinguish animals based on their body heat and being able to detect
animals at night. However, the use of drone-mounted thermal infrared cameras
comes with several technical challenges. In this paper we address some of these
issues, namely thermal contrast problems due to heat from the ground,
absorption and emission of thermal infrared radiation by the atmosphere,
obscuration by vegetation, and optimizing the flying height of drones for a
best balance between covering a large area and being able to accurately image
and identify animals of interest. We demonstrate the application of these
methods with a case study using field data, and make the first ever detection
of the critically endangered riverine rabbit (Bunolagus monticularis) in
thermal infrared data. We provide a web-tool so that the community can easily
apply these techniques to other studies
(http://www.astro.ljmu.ac.uk/~aricburk/uav_calc/).
