Data from: Drones count wildlife more accurately and precisely than humans

Knowing how many individuals are in a wildlife population allows informed
management decisions to be made. Ecologists are increasingly using
technologies, such as remotely piloted aircraft (RPA; commonly known as
“drones,” unmanned aerial systems or unmanned aerial vehicles), for
wildlife monitoring applications. Although RPA are widely touted as a
cost-effective way to collect high-quality wildlife population data, the
validity of these claims is unclear. Using life-sized, replica seabird
colonies containing a known number of fake birds, we assessed the accuracy
of RPA-facilitated wildlife population monitoring compared to the
traditional ground-based counting method. The task for both approaches was
to count the number of fake birds in each of 10 replica seabird colonies.
We show that RPA-derived data are, on average, between 43% and 96% more
accurate than the traditional ground-based data collection method. We also
demonstrate that counts from this remotely sensed imagery can be
semi-automated with a high degree of accuracy. The increased accuracy and
increased precision of RPA-derived wildlife monitoring data provides
greater statistical power to detect fine-scale population fluctuations
allowing for more informed and proactive ecological management.