Automated monitoring for birds in flight: Proof of concept with eagles at a wind power facility

Abstract

Automated surveys for wildlife have the potential to improve data collection while averting mortality of animals. Collisions of eagles at wind power facilities are particularly of concern and therefore an automated system that could detect birds, determine if they are eagles, and track their movement, might aid in curtailing wind turbines before collisions occur. Here, we use human observers and photographs to test the ability of a camera-based monitoring system, called IdentiFlight, to detect, classify, and track birds. IdentiFlight detected 96% of the bird flights detected by observers and detected 562% more birds than did observers. The discrepancy between observers and IdentiFlight seemed to be because the ability of observers to detect birds declined sharply by distance and toward the west. We reviewed photographs taken by IdentiFlight and determined that IdentiFlight misclassified nine of 149 eagles as non-eagles for a false negative rate of 6%, and 287 of 1013 non-eagles as eagles for a false positive rate of 28%. The median distance at classification for birds classified as eagles was 793 m and the median time from detection till classification was 0.4 s. Collectively, our results suggest that automated cameras can be effective means of detecting birds in flight and identifying eagles.