Reduction of Species Identification Errors in Surveys of Marine Wildlife Abundance Utilising Unoccupied Aerial Vehicles (UAVs)

Eyal Bigal, Ori Galili, Itai van Rijn, Massimiliano Rosso, Christophe Cleguer, Amanda Hodgson, Aviad Scheinin, Dan Tchernov

Research output: Contribution to journalArticlepeer-review


The advent of unoccupied aerial vehicles (UAVs) has enhanced our capacity to survey wildlife abundance, yet new protocols are still required for collecting, processing, and analysing image-type observations. This paper presents a methodological approach to produce informative priors on species misidentification probabilities based on independent experiments. We performed focal follows of known dolphin species and distributed our imagery amongst 13 trained observers. Then, we investigated the effects of reviewer-related variables and image attributes on the accuracy of species identification and level of certainty in observations. In addition, we assessed the number of reviewers required to produce reliable identification using an agreement-based framework compared with the majority rule approach. Among-reviewer variation was an important predictor of identification accuracy, regardless of previous experience. Image resolution and sea state exhibited the most pronounced effects on the proportion of correct identifications and the reviewers’ mean level of confidence. Agreement-based identification resulted in substantial data losses but retained a broader range of image resolutions and sea states than the majority rule approach and produced considerably higher accuracy. Our findings suggest a strong dependency on reviewer-related variables and image attributes, which, unless considered, may compromise identification accuracy and produce unreliable estimators of abundance.

Original languageEnglish
Article number4118
Pages (from-to)4118
Number of pages1
JournalRemote Sensing
Issue number16
StatePublished - 22 Aug 2022


  • aerial surveys
  • cetaceans
  • dolphins
  • drones
  • false positive detections
  • marine mammals
  • misclassification
  • trial experiments

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)


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