RESEARCH ARTICLE Using virtual reality and thermal imagery to improve statistical modelling of vulnerable and protected species 1,2,3 1☯ 1☯ 1☯ 4 Catherine LeighID *, Grace Heron , Ella Wilson , Taylor Gregory , Samuel Clifford , Jacinta Holloway1, Miles McBain1, Felipe Gonzalez5,6, James McGree1,3, Ross Brown1,7, Kerrie Mengersen1,3, Erin E. Peterson1,2,3 1 ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Australia, 2 Institute for Future Environments, Queensland University of Technology, Brisbane, Australia, 3 School of Mathematical a1111111111 Sciences, Science and Engineering Faculty, Queensland University of Technology. Brisbane, Australia, a1111111111 4 London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom, 5 School of a1111111111 Electrical Engineering and Computer Science, Science and Engineering Faculty, Queensland University of a1111111111 Technology. Brisbane, Australia, 6 ARC Centre of Excellence for Robotic Vision (ACRV), Australia, 7 School a1111111111 of Electrical Engineering and Computer Science, Science and Engineering Faculty, Queensland University of Technology. Brisbane, Australia ☯ These authors contributed equally to this work. *
[email protected] OPEN ACCESS Citation: Leigh C, Heron G, Wilson E, Gregory T, Abstract Clifford S, Holloway J, et al. (2019) Using virtual reality and thermal imagery to improve statistical Biodiversity loss and sparse observational data mean that critical conservation decisions modelling of vulnerable and protected species. PLoS ONE 14(12): e0217809. https://doi.org/ may be based on little to no information. Emerging technologies, such as airborne thermal 10.1371/journal.pone.0217809 imaging and virtual reality, may facilitate species monitoring and improve predictions of spe- Editor: Stephanie S. Romanach, U.S.