Unmanned aerial vehicles for surveying marine fauna: assessing detection probability

Abstract 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 ( UAV s) offer an alternative with man...

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Bibliographic Details
Published in:Ecological Applications
Main Authors: Hodgson, Amanda, Peel, David, Kelly, Natalie
Other Authors: Australian Marine Mammal Centre, Woodside Energy
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2017
Subjects:
Online Access:http://dx.doi.org/10.1002/eap.1519
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Feap.1519
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/eap.1519
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Summary:Abstract 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 ( UAV s) 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. UAV s 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 UAV s are an effective alternative to traditional methods, providing a detection probability ...