Imperfect detection and wildlife density estimation using aerial surveys with infrared and visible sensors

Abstract

Abstract Aerial vehicles equipped with infrared thermal sensors facilitate quick density estimates of wildlife, but detection error can arise from the thermal sensor and viewer of the infrared video. We reviewed published research to determine how commonly these sources of error have been assessed in studies using infrared video from aerial platforms to sample wildlife. The number of annual articles pertaining to aerial sampling using infrared thermography has increased drastically since 2018, but past studies inconsistently assessed sources of imperfect detection. We illustrate the importance of accounting for some of these types of error in a case study on white‐tailed deer Odocoileus virginianus in Indiana, USA, using a simple double‐observer approach. In our case study, we found evidence of false negatives associated with the viewer of infrared video. Additionally, we found that concordance between the detections of two viewers increased when using a red‐green‐blue camera paired with the infrared thermal sensor, when altitude decreased and when more stringent criteria were used to classify thermal signatures as deer. We encourage future managers and ecologists recording infrared video from aerial platforms to use double‐observer methods to account for viewer‐induced false negatives when video is manually viewed by humans. We also recommend combining infrared video with red‐green‐blue video to reduce false positives, applying stringent verification standards to detections in infrared and red‐green‐blue video and collecting data at lower altitudes over snow when needed.

Keywords

• Density estimation
• detection error
• drones
• infrared video
• Odocoileus virginianus
• thermal sensor