Unmanned aerial vehicles for surveying marine fauna: assessing detection probability.
Aerial surveys are conducted for various fauna to assess abundance, distribution, and habitat use over large spatial scales. They are traditionally conducted using light aircraft with observers recording sightings in real time. Unmanned Aerial Vehicles (UAVs) offer an alternative with many potential advantages, including eliminating human risk. To be effective, this emerging platform needs to provide detection rates of animals comparable to traditional methods. UAVs can also acquire new types of information, and this new data requires a reevaluation of traditional analyses used in aerial surveys; including estimating the probability of detecting animals. We conducted 17 replicate UAV surveys of humpback whales (Megaptera novaeangliae) while simultaneously obtaining a 'census' of the population from land-based observations, to assess UAV detection probability. The ScanEagle UAV, carrying a digital SLR camera, continuously captured images (with 75% overlap) along transects covering the visual range of land-based observers. We also used ScanEagle to conduct focal follows of whale pods (n = 12, mean duration = 40 min), to assess a new method of estimating availability. A comparison of the whale detections from the UAV to the land-based census provided an estimated UAV detection probability of 0.33 (CV = 0.25; incorporating both availability and perception biases), which was not affected by environmental covariates (Beaufort sea state, glare, and cloud cover). According to our focal follows, the mean availability was 0.63 (CV = 0.37), with pods including mother/calf pairs having a higher availability (0.86, CV = 0.20) than those without (0.59, CV = 0.38). The follows also revealed (and provided a potential correction for) a downward bias in group size estimates from the UAV surveys, which resulted from asynchronous diving within whale pods, and a relatively short observation window of 9 s. We have shown that UAVs are an effective alternative to traditional methods, providing a detection probability that is within the range of previous studies for our target species. We also describe a method of assessing availability bias that represents spatial and temporal characteristics of a survey, from the same perspective as the survey platform, is benign, and provides additional data on animal behavior.
Murdoch University Cetacean Research Unit, School of Veterinary and Life Sciences, Murdoch University, South Street, Murdoch, Western Australia, 6150, Australia.
Amanda
A
Hodgson
CSIRO Data61, Castray Esplanade, Hobart, Tasmania, 7000, Australia.
David
D
Peel
CSIRO Data61, Castray Esplanade, Hobart, Tasmania, 7000, Australia.
Natalie
N
Kelly
D000401:Aircraft; D000818:Animals; D059001:Aquatic Organisms; D003625:Data Collection / Q000379:methods*; D011336:Probability; D011793:Queensland; D058998:Remote Sensing Technology / Q000379:methods*
abundance; aerial survey; availability; behavior; cetaceans; digital photography; drones; images; unmanned aerial systems; unmanned aircraft systems