Implementing Thermal Imaging Devices Equipped to Small Unmanned Aerial Systems (sUAS) to Detect Grassland Bird Nests.

Grassland bird populations are declining at greater rates than any other group of birds. A well-established method of monitoring rapidly disappearing populations is by locating and identifying active bird nests. Studies quantifying grassland birds tend to have low statistical power due to low sample sizes, high labor costs, and high levels of disturbance - associated with difficulty finding nests. However, advances in unmanned aerial vehicles (UAVs) and thermographic imaging technologies have potential to improve efficiency of locating nests, while causing minimal disruption. Early research has evaluated nest detectability using a thermal imaging system equipped to a UAV. The UAV was flown at three different altitudes to detect simulated nests at incremental depths in monoculture grass stand canopies. This study evaluated nest detection accuracy using two different methods. The first required creating a flight plan for map construction of the research area using third-party software to later identify nests by heat signatures within the map. The second method required analyzing recordings of real-time video feed to identify and pin-point nest locations. Both methodologies were tested in a blind evaluation method, using multiple test subjects and replications. Results from this study have suggested that mapping software does not optimize nest detectability and identification. Future research will implement video analysis of UAV flights for nest detection in reclaimed native grasslands. This will allow for quantification of use and fitness of reclaimed native grasslands as habitat for grassland bird populations.