Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/112407
Citations
Scopus Web of Science® Altmetric
?
?
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHodgson, J.en
dc.contributor.authorMott, R.en
dc.contributor.authorBaylis, S.en
dc.contributor.authorPham, T.en
dc.contributor.authorWotherspoon, S.en
dc.contributor.authorKilpatrick, A.en
dc.contributor.authorRaja Segaran, R.en
dc.contributor.authorReid, I.en
dc.contributor.authorTerauds, A.en
dc.contributor.authorKoh, L.en
dc.date.issued2018en
dc.identifier.citationMethods in Ecology and Evolution, 2018; 9(5):1160-1167en
dc.identifier.issn2041-210Xen
dc.identifier.issn2041-210Xen
dc.identifier.urihttp://hdl.handle.net/2440/112407-
dc.description.abstract1. 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. 2. 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. 3. 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. 4. 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.en
dc.description.statementofresponsibilityJarrod C. Hodgson, Rowan Mott, Shane M. Baylis, Trung T. Pham, Simon Wotherspoon, Adam D. Kilpatrick, Ramesh Raja Segaran, Ian Reid, Aleks Terauds, Lian Pin Kohen
dc.language.isoenen
dc.publisherJohn Wiley and Sonsen
dc.rights© 2018 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en
dc.subjectBird; drones; ecology; population monitoring; remotely piloted aircraft; surveys; unmanned aerial vehicle; wildlifeen
dc.titleDrones count wildlife more accurately and precisely than humansen
dc.typeJournal articleen
dc.identifier.rmid0030083117en
dc.identifier.doi10.1111/2041-210X.12974en
dc.identifier.pubid398173-
pubs.library.collectionEcology, Evolution and Landscape Science publicationsen
pubs.library.teamDS03en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidHodgson, J. [0000-0003-0481-7360]en
dc.identifier.orcidRaja Segaran, R. [0000-0002-0484-8194]en
dc.identifier.orcidReid, I. [0000-0001-7790-6423]en
Appears in Collections:Ecology, Evolution and Landscape Science publications

Files in This Item:
File Description SizeFormat 
hdl_112407.pdfPublished version871.2 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.