# Optimising observing strategies for monitoring animals using   drone-mounted thermal infrared cameras

**Authors:** Claire Burke, Maisie Rashman, Serge Wich, Andy Symons, Cobus Theron,, Steve Longmore

arXiv: 1812.05498 · 2019-02-20

## TL;DR

This paper explores how to optimize drone-mounted thermal infrared cameras for wildlife monitoring, addressing technical challenges and demonstrating a case study including the first detection of a critically endangered rabbit species.

## Contribution

It introduces methods to improve thermal infrared imaging from drones, including a web-tool for community use, and presents the first detection of the riverine rabbit using this technology.

## Key findings

- Demonstrated first thermal infrared detection of the riverine rabbit.
- Developed techniques to mitigate thermal contrast and atmospheric effects.
- Provided a web-tool for optimizing drone thermal imaging strategies.

## Abstract

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/).

## Full text

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## Figures

35 figures with captions in the complete paper: https://tomesphere.com/paper/1812.05498/full.md

## References

43 references — full list in the complete paper: https://tomesphere.com/paper/1812.05498/full.md

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Source: https://tomesphere.com/paper/1812.05498