Revue des applications et de l’utilité des drones en conservation de la faune

Charbonneau, Patrick; Lemaître, Jérôme

doi:https://doi.org/10.7202/1080620ar

Feuilleter les articles de ce numéro

Louis Fortier, O.C., O.Q. (1953-2020) : océanographe et grand mobilisateur de la recherche nordique

Reproduction de l’esturgeon jaune dans la rivière Saint-François : un exemple de participation des peuples autochtones à la conservation d’une espèce emblématique

Plan de l’article

Retour au début
Résumé
Texte intégral (PDF)Texte intégral (PDF)
Remerciements
Notes biographiques
Bibliographie

Boîte à outils

Sauvegarder Supprimer
PDFTélécharger
Citer cet article
Partager

Résumés

Résumé

Les drones deviennent de plus en plus accessibles et performants. La présente synthèse passe en revue la littérature scientifique récente traitant de l’utilisation des drones pour étudier la faune. Nous avons classé 250 références selon 4 applications : inventaires fauniques, réponse comportementale de la faune face aux drones, éthologie et protection de la faune. Notre revue indique que les drones offrent un fort potentiel pour inventorier la faune, en particulier les oiseaux et les mammifères, et que des développements sont en cours pour la faune aquatique, l’herpétofaune et l’entomofaune. Nous exposons aussi les principaux effets des drones sur la faune et, à la lumière des informations obtenues, nous émettons des recommandations préliminaires pour limiter le dérangement de celle-ci. Les avantages des drones sont multiples, et le développement rapide de la technologie laisse croire que plusieurs limites actuelles seront écartées prochainement. Enfin, nous exposons quelques éléments de la réglementation canadienne sur l’usage des drones. En conclusion, les drones pourraient jouer un rôle prépondérant à moyen terme en conservation de la biodiversité.

Mots-clés :

comportement,
conservation,
détection,
drone,
inventaire

Abstract

Drones are becoming more accessible and efficient. This article presents a review of recent scientific literature focusing on their use to study wildlife. The 250 publications consulted were grouped into one of 4 categories: wildlife surveys, the behavioural response of wildlife to drones, the study of wildlife behaviour and wildlife protection. The review highlighted the great potential of drones for helping in the survey of animals, especially birds and mammals, and it also revealed the developments underway to allow their use for studying aquatic fauna, amphibians, reptiles and insects. The main impacts of drones on animals are presented and, based on the available information, preliminary recommendations are made to limit their disturbance to wildlife. Drones have multiple advantages and the rapid development of this technology suggests that several of the current limits to their use will soon be overcome. Finally, elements of the Canadian regulations on the use of drones are presented. In conclusion, in the medium-term, drones have the potential to play a significant role in the protection and management of biodiversity.

Keywords:

behaviour,
conservation,
detection,
drone,
survey

Veuillez télécharger l’article en PDF pour le lire.

Télécharger

Parties annexes

Remerciements

Nous tenons à remercier Francis Bédard, Marc Bélanger, Geneviève Bourget, Anne-Marie Gosselin, Jean Lapointe, Louis-Philippe Lapointe, Sébastien Lefort, Denis Manningham, Antoine Nappi, Danielle St-Pierre, les membres anonymes du comité de révision ainsi que l’équipe d’édition du Naturaliste canadien pour leurs commentaires sur le manuscrit.

Notes biographiques

Patrick Charbonneau (M. Sc.) est biologiste et pilote de drone certifié au ministère des Forêts, de la Faune et des Parcs (MFFP).

Jérôme Lemaître (Ph. D.) est biologiste-chercheur en avifaune au MFFP.

Bibliographie

Abd-Elrahman, A., L. Pearlstine et F. Percival, 2005. Development of pattern recognition algorithm for automatic bird detection from unmanned aerial vehicle imagery. Surveying and Land Information Science, 65 (1) : 37-45.
10.1002/ecs2.2163 Google Scholar
Allan, B.M., D.G. Nimmo, D. Ierodiaconou, J. VanDerWal, L.P. Koh et E.G. Ritchie, 2018. Futurecasting ecological research: The rise of technoecology. Ecosphere, 9 : e02163. https://doi.org/10.1002/ecs2.2163.
10.1002/ecs2.2163 Google Scholar
Anderson, K. et K.J. Gaston, 2013. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology and the Environment, 11 : 138-146.
10.1890/120150 Google Scholar
Apprill, A., C.A. Miller, M.J. Moore, J.W. Durban, H. Fearnbach et L.G. Barrett-Lennard, 2017. Extensive core microbiome in drone-captured whale blow supports a framework for health monitoring. mSystems, 2 : e00119-17. https://doi.org/10.1128/mSystems.00119-17.
10.1128/mSystems.00119-17 Google Scholar
Arona, L., J. Dale, S.G. Heaslip, M.O. Hammill et D.W. Johnston, 2018. Assessing the disturbance potential of small unoccupied aircraft systems (UAS) on gray seals (Halichoerus grypus) at breeding colonies in Nova Scotia, Canada. PeerJ, 6 : e4467. https://doi.org/10.7717/peerj.4467.
10.7717/peerj.4467 Google Scholar
Aubry, K.B., C.M. Raley et K.S. McKelvey, 2017. The importance of data quality for generating reliable distribution models for rare, elusive, and cryptic species. PLoS ONE, 12 (6) : e0179152. https://doi.org/10.1371/journal.pone.0179152.
10.1371/journal.pone.0179152 Google Scholar
Balestrieri, E., P. Daponte, L. De Vito et F. Lamonaca, 2021. Sensors and measurements for unmanned systems: An overview. Sensors, 21 : 1518. https://doi.org/10.3390/s21041518.
10.3390/s21041518 Google Scholar
Barasona, J.A., M. Mulero-Pázmány, P. Acevedo, J.J. Negro, M.J. Torres, C. Gortázar et J. Vicente, 2014. Unmanned aircraft systems for studying spatial abundance of ungulates: Relevance to spatial epidemiology. PLoS ONE, 9 : e115608. https://doi.org/10.1371/journal.pone.0115608.
10.1371/journal.pone.0115608 Google Scholar
Barbedo, J.G.A., L.V. Koenigkan, T. T. Santos et P.M. Santos, 2019. A study on the detection of cattle in UAV images using deep learning. Sensors, 19 : 5436. https://doi.org/10.3390/s19245436.
10.3390/s19245436 Google Scholar
Barnas, A.F., C.J. Felege, R.F. Rockwell et S.N. Ellis-Felege, 2018a. A pilot(less) study on the use of an unmanned aircraft system for studying polar bears (Ursus maritimus). Polar Biology, 41 : 1055-1062. https://doi.org/10.1007/s00300-018-2270-0.
10.1007/s00300-018-2270-0 Google Scholar
Barnas, A.F., R. Newman, C.J. Felege, M.P. Corcoran, S.D. Hervey, T.J. Stechmann, R.F. Rockwell et S.N. Ellis-Felege, 2018 b. Evaluating behavioral responses of nesting lesser snow geese to unmanned aircraft surveys. Ecology and Evolution, 8 : 1328-1338. https://doi.org/10.1002/ece3.3731.
10.1002/ece3.3731 Google Scholar
Barr, J.R., M.C. Green, S.J. DeMaso et T.B. Hardy, 2020. Drone surveys do not increase colony-wide flight behavior at waterbird nesting sites, but sensitivity varies among species. Scientific Reports, 10 : 3781. https://doi.org/10.1038/s41598-020-60543-z.
10.1038/s41598-020-60543-z Google Scholar
Beaver, J.T., R.W. Baldwin, M. Messinger, C.H. Newbolt, S.S. Ditchkoff et M.R. Silman, 2020. Evaluating the use of drones equipped with thermal sensors as an effective method for estimating wildlife. Wildlife Society Bulletin, 44 (2) : 434-443. https://doi.org/10.1002/wsb.1090.
10.1002/wsb.1090 Google Scholar
Bennitt, E., H.L.A. Bartlam-Brooks, T.Y. Hubel et A.M. Wilson, 2019. Terrestrial mammalian wildlife responses to unmanned aerial systems approaches. Scientific Reports, 9 : 2142. https://doi.org/10.1038/s41598-019-38610-x.
10.1038/s41598-019-38610-x Google Scholar
Bergenas, J., R. Stohl et A. Georgieff, 2013. The other side of drones: Saving wildlife in Africa and managing global crime. Conflict Trends, 3 : 3-9.
10.1038/s41598-017-18202-3 Google Scholar
Bevan, E., T. Wibbels, B.M.Z. Najera, M.A.C. Martine, L.A.M. Sarti, F.I. Martinez, J.M. Cuevas, T. Anderson, A. Bonka, M.H. Hernandez, L.J. Pena et P.M. Burchfield, 2015. Unmanned aerial vehicles (UAVs) for monitoring sea turtles in near-shore waters. Marine Turtle Newsletter, 145 : 19-22.
10.3390/drones3020041 Google Scholar
Bevan, E., T. Wibbels, E. Navarro, M. Rosas, B.M.Z. Najera, L. Sarti, F. Illescas, J. Montano, L.J. Peña et P. Burchfield, 2016. Using unmanned aerial vehicle (UAV) technology for locating, identifying, and monitoring courtship and mating behavior in the green turtle (Chelonia mydas). Herpetological Review, 47 : 27-32.
10.1080/01431161.2018.1558372 Google Scholar
Bevan, E., S. Whiting, T. Tucker, M. Guinea, A. Raith et R. Douglas, 2018. Measuring behavioral responses of sea turtles, saltwater crocodiles, and crested terns to drone disturbance to define ethical operating thresholds. PLoS ONE, 13 (3) : e0194460. https://doi.org/10.1371/journal.pone.0194460.
10.1371/journal.pone.0194460 Google Scholar
Bird, D.M. et K.L. Bildstein, 2007. Raptor research and management techniques. Raptor Research Foundation, Surrey, B.C., 463 p.
10.1675/063.035.0119 Google Scholar
Biserkov, V.Y. et S.P. Lukanov, 2017. Unmanned aerial vehicles (UAVs) for surveying freshwater turtle populations: Methodology adjustment. Acta Zoologica Bulgarica, (Supplement 10) : 161-163.
10.1371/journal.pone.0122588 Google Scholar
Brisson-Curadeau, É., D. Bird, C. Burke, D.A. Fifield, P. Pace, R.B. Sherley et K.H. Elliott, 2017. Seabird species vary in behavioural response to drone census. Scientific Reports, 7 : 17884. https://doi.org/10.1038/s41598-017-18202-3.
10.1038/s41598-017-18202-3 Google Scholar
[BES] British Ecological Society, 2018. Drones can detect protected nightjar nests. Disponible en ligne à : https://www.britishecologicalsociety.org/drones-nightjar-nests/. [Visité le 2021-04-20].
10.1002/aqc.2654 Google Scholar
Brunton, E., J. Bolin, J. Leon et S. Burnett, 2019. Fright or flight? Behavioural responses of kangaroos to drone-based monitoring. Drones, 3 : 41. https://doi.org/10.3390/drones3020041.
10.3390/drones3020041 Google Scholar
Burke, C., M. Rashman, S. Wich, A. Symons, C. Theron et S. Longmore, 2019. Optimizing observing strategies for monitoring animals using drone-mounted thermal infrared cameras. International Journal of Remote Sensing, 40 : 439-467.
10.1080/01431161.2018.1558372 Google Scholar
Bushaw, J.D., K.M. Ringelman et F.C. Rohwer, 2019. Applications of unmanned aerial vehicles to survey mesocarnivores. Drones, 3 : 28. https://doi.org/.
10.3390/drones3010028 Google Scholar
Calvo, K., 2017. Drones for conservation—Field guide for photographers, researchers, conservationists and archaeologists. Dronesforconservation.org. 89 p.
10.1016/j.cub.2015.07.024 Google Scholar
Chabot, D., 2009. Systematic evaluation of a stock unmanned aerial vehicle (UAV) system for small-scale wildlife survey applications. Mémoire de maîtrise, Department of Natural Resource Sciences, McGill University, Montréal, 79 p. + annexes.
10.1093/conphys/coy067 Google Scholar
Chabot, D. et D.M. Bird, 2012. Evaluation of an off-the-shelf unmanned aircraft system for surveying flocks of geese. Waterbirds, 35 (1) : 170-174.
10.1675/063.035.0119 Google Scholar
Chabot, D., S.R. Craik et D.M. Bird, 2015. Population census of a large common tern colony with a small unmanned aircraft. PLoS ONE, 10 (4) : e0122588. https://doi.org/.
10.1371/journal.pone.0122588 Google Scholar
Chabot, D., S. Stapleton et C.M. Francis, 2019. Measuring the spectral signature of polar bears from a drone to improve their detection from space. Biological Conservation, 237 : 125-132. https://doi.org/10.1016/j.biocon.2019.06.022.
10.1016/j.biocon.2019.06.022 Google Scholar
Chirayath, V. et S.A. Earle. 2016. Drones that see through waves—Preliminary results from airborne fluid lensing for centimeter-scale aquatic conservation. Aquatic Conservation: Marine and Freshwater Ecosystems, 26 (Supplement 2) : 237-250. https://doi.org/10.1002/aqc.2654.
10.1002/aqc.2654 Google Scholar
Christiansen, F., F. Vivier, C. Charlton, R. Ward, A. Amerson, S. Burnell et L. Bejder, 2018. Maternal body size and condition determine calf growth rates in southern right whales. Marine Ecology Progress Series, 592 : 267-281. https://doi.org/10.3354/meps12522.
10.3354/meps12522 Google Scholar
Christie, K.S., S.L. Gilbert, C.L. Brown, M. Hatfield et L. Hanson, 2016. Unmanned aircraft systems in wildlife research: Current and future applications of a transformative technology. Frontiers in Ecology and the Environment, 14 (5) : 241-251. https://doi.org/.
10.1002/fee.1281 Google Scholar
Daniels, K., 2018. Inferences about the conservation utility of using unmanned aerial vehicles to conduct rapid assessments for basking freshwater turtles. Mémoire de maîtrise soumis à la Faculty of Environmental Science, University of Tennessee, Chattanooga, Tennessee, É.-U., 40 p. + annexes.
10.1016/j.neubiorev.2005.03.027 Google Scholar
D’hont, B., K. Calders, H. Bartholomeus, T. Whiteside, R. Bartolo, S. Levick, S.M. KrishnaMoorthy, L. Terryn et H. Verbeeck, 2021. Characterising termite mounds in a tropical savanna with UAV laser scanning. Remote Sensing, 13 : 476. https://doi.org/10.3390/rs13030476.
10.3390/rs13030476 Google Scholar
Ditmer, M.A., J.B. Vincent, L.K. Werden, J.C. Tanner, T.G. Laske, P.A. Iaizzo, D.L. Garshelis et J.R. Fieberg, 2015. Bears show a physiological but limited behavioral response to unmanned aerial vehicles. Current Biology, 25 : 2278-2283. http://dx.doi.org/10.1016/j.cub.2015.07.024.
10.1016/j.cub.2015.07.024 Google Scholar
Ditmer, M.A., L.K. Werden, J.C. Tanner, J.B. Vincent, P. Callahan, P.A. Iaizzo, T.G. Laske, et D.L. Garshelis, 2018. Bears habituate to the repeated exposure of a novel stimulus, unmanned aircraft systems. Conservation Physiology, 6 (1) : coy067. https://doi.org/10.1093/conphys/coy067.
10.1093/conphys/coy067 Google Scholar
Domínguez-Sánchez, C.A., K.A. Acevedo-Whitehouse et D. Gendron, 2018. Effect of drone-based blow sampling on blue whale (Balaenoptera musculus) behavior. Marine Mammal Science. https://doi.org/10.1111/mms.12482.
10.1111/mms.12482 Google Scholar
Drever, M.C., D. Chabot, P.D. O’Hara, J.D. Thomas, A. Breault et R.L. Millikin, 2015. Evaluation of an unmanned rotorcraft to monitor wintering waterbirds and coastal habitats in British Columbia, Canada. Journal of Unmanned Vehicle Systems, 3 : 256-267. http://dx.doi.org/10.1139/juvs-2015-0019.
10.1139/juvs-2015-0019 Google Scholar
Dufresnes, C., J. Golay, J. Schuerch, T. Dejean et S. Dubey, 2020. Monitoring of the last stronghold of native pool frogs (Pelophylax lessonae) in Western Europe, with implications for their conservation. European Journal of Wildlife Research 66 (3) : 45. https://doi.org/10.1007/s10344-020-01380-3.
10.1007/s10344-020-01380-3 Google Scholar
Durban, J.W., H. Fearnbach, L.G. Barrett-Lennard, W.L. Perryman et D.J. LeRoi, 2015. Photogrammetry of killer whales using a small hexacopter launched at sea. Journal of Unmanned Vehicle Systems, 3 : 1-5. http://dx.doi.org/10.1139/juvs-2015-0020.
10.1139/juvs-2015-0020 Google Scholar
Durban, J.W., M.J. Moore, G. Chiang, L.S. Hickmott, A. Bocconcelli, G. Howes, P.A. Bahamonde, W.L. Perryman et D.J. LeRoi, 2016. Photogrammetry of blue whales with an unmanned hexacopter. Marine Mammal Science, 32 : 1510-1515. https://doi.org/10.1111/mms.12328.
10.1111/mms.12328 Google Scholar
Edney, A.J. et M.J. Wood, 2021. Applications of digital imaging and analysis in seabird monitoring and research. Ibis, 163 : 317-337. https://doi.org/10.1111/ibi.12871.
10.1111/ibi.12871 Google Scholar
Eilam, D., 2005. Die hard: A blend of freezing and fleeing as a dynamic defense—implications for the control of defensive behavior. Neuroscience and Biobehavioral Reviews, 29 : 1181-1191. https://doi.org/10.1016/j.neubiorev.2005.03.027.
10.1016/j.neubiorev.2005.03.027 Google Scholar
Eilam, D., R. Izhar et J. Mort, 2011. Threat detection: Behavioral practices in animals and humans. Neuroscience and Biobehavioral Reviews, 35 : 999-1006. https://doi.org/10.1016/j.neubiorev.2010.08.002.
10.1016/j.neubiorev.2010.08.002 Google Scholar
Elsey, R.M. et P.L. Trosclair III, 2016. The use of an unmanned aerial vehicle to locate alligator nests. Southeastern Naturalist, 15 (1) : 76-82.
10.1656/058.015.0106 Google Scholar
Erbe, C., M. Parsons, A.J. Duncan, S.K. Osterrieder et K. Allen, 2017. Aerial and underwater sound of unmanned aerial vehicles (UAV, drones). Journal of Unmanned Vehicle Systems, 5 : 92-101. https://doi.org/10.1139/juvs-2016-0018.
10.1139/juvs-2016-0018 Google Scholar
Escobar, J.E.C., M. Rollins et S. Unger, 2021. Preliminary data on an affordable UAV system to survey for freshwater turtles: Advantages and disadvantages of low-cost drones. Journal of Unmanned Vehicle Systems, 9 : 67-74. http://dx.doi.org/10.1139/juvs-2018-0037.
10.1139/juvs-2018-0037 Google Scholar
Evans, L.J., T.H. Jones, K. Pang, M.N. Evans, S. Saimin et B. Goossens, 2015. Use of drone technology as a tool for behavioral research: A case study of crocodilian nesting. Herpetological Conservation and Biology, 10 (1) : 90-98.
10.1139/facets-2016-0019 Google Scholar
Ezat, M.A., C.J. Fritsch et C.T. Downs, 2018. Use of an unmanned aerial vehicle (drone) to survey Nile crocodile populations: A case study at Lake Nyamithi, Ndumo Game Reserve, South Africa. Biological Conservation, 223 : 76-81. https://doi.org/10.1016/j.biocon.2018.04.032.
10.1016/j.biocon.2018.04.032 Google Scholar
Faye, E., F Rebaudo, D. Yánez-Cajo, S. Cauvy-Fraunié et O. Dangles, 2016. A toolbox for studying thermal heterogeneity across spatial scales: From unmanned aerial vehicle imagery to landscape metrics. Methods in Ecology and Evolution, 7 : 437-446. https://doi.org/10.1111/2041-210X.12488.
10.1111/2041-210X.12488 Google Scholar
Francis, R.J., M.B. Lyons, R.T. Kingsford et K.J. Brandis, 2020. Counting mixed breeding aggregations of animal species using drones: Lessons from waterbirds on semi-automation. Remote Sensing, 12 (7) : 1185. https://doi.org/10.3390/rs12071185.
10.3390/rs12071185 Google Scholar
Fu, Y., M. Kinniry et L.N. Kloepper, 2018. The Chirocopter: A UAV for recording sound and video of bats at altitude. Methods in Ecology and Evolution, 9 : 1531-1535. https://doi.org/10.1111/2041-210X.12992.
10.1111/2041-210X.12992 Google Scholar
Gallagher, A.J., Y.P. Papastamatiou et A. Barnett, 2018. Apex predatory sharks and crocodiles simultaneously scavenge a whale carcass. Journal of Ethology, 36 : 205-209. https://doi.org/10.1007/s10164-018-0543-2.
10.1007/s10164-018-0543-2 Google Scholar
Gentle, M., N. Finch, J. Speed et A. Pople, 2018. A comparison of unmanned aerial vehicles (drones) and manned helicopters for monitoring macropod populations. Wildlife Research, 45 (7) : 586-594. https://doi.org/10.1071/WR18034.
10.1071/WR18034 Google Scholar
Goebel, M.E., W.L. Perryman, J.T. Hinke, D.J. Krause, N.A. Hann, S. Gardner et D.J. LeRoi, 2015. A small unmanned aerial system for estimating abundance of and size of Antarctic predators. Polar Biology. https://doi.org/10.1007/s00300-014-1625-4.
10.1007/s00300-014-1625-4 Google Scholar
Goldbogen, J.A., D.E. Cade, J. Calambokidis, A.S. Friedlaender, J. Potvin, P.S. Segre et A.J. Werth, 2017. How baleen whales feed: The biomechanics of engulfment and filtration. Annual Review of Marine Science, 9 : 367-386. https://doi.org/10.1146/annurev-marine-122414-033905.
10.1146/annurev-marine-122414-033905 Google Scholar
Gonzalez, L.F., G.A. Montes, E. Puig, S. Johnson, K. Mengersen et K.J. Gaston, 2016. Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors, 16 (1) : 97. https://doi.org/10.3390/s16010097.
10.3390/s16010097 Google Scholar
Gouvernement du Canada, 2019a. Utilisation de véhicules aériens sans pilote (drones) dans les parcs nationaux du Canada. Disponible en ligne à : https://www.pc.gc.ca/fr/pn-np/ab/banff/info/permis- permit/drone. [Visité le 2020-07-07].
10.1007/s13364-018-0400-2 Google Scholar
Gouvernement du Canada, 2019b. Sécurité des drones. Disponible en ligne à : https://www.tc.gc.ca/fr/services/aviation/securite-drones.html. [Visité le 2020-04-15].
10.1111/eth.12966 Google Scholar
Grenzdörffer, G.J., 2013. UAS-based automatic bird count of a common gull colony. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-1/W2 : 169-174. https://doi.org/10.5194/isprsarchives-XL-1-W2-169-2013.
10.5194/isprsarchives-XL-1-W2-169-2013 Google Scholar
Groves, P.A., B. Alcorn, M.M. Wiest, J.M. Maselko et W.P. Connor, 2016. Testing unmanned aircraft systems for salmon spawning surveys. FACETS, 1 : 187-204. https://doi.org/10.1139/facets-2016-0019.
10.1139/facets-2016-0019 Google Scholar
Hanson, L., C.L. Holmquist-Johnson et M.L. Cowardin, 2014. Evaluation of the Raven sUAS to detect and monitor greater sage-grouse leks within the Middle Park population. U.S. Geological Survey Open-File Report 2014-1205, Reston, Virginia, 20 p.
10.3133/ofr20141205 Google Scholar
Harris, C.M., H. Herata et F. Hertel, 2019. Environmental guidelines for operation of Remotely Piloted Aircraft Systems (RPAS): Experience from Antarctica. Biological Conservation, 236 : 521-531. https://doi.org/10.1016/j.biocon.2019.05.019.
10.1016/j.biocon.2019.05.019 Google Scholar
Hensel, E., S. Wenclawski et C.A. Layman, 2018. Using a small, consumer-grade drone to identifiy and count marine megafauna in shallow habitats. Latin American Journal of Aquatic Research, 46 (5) : 1025-1033.
10.3856/vol46-issue5-fulltext-15 Google Scholar
Hodgson, A., N. Kelly et D. Peel, 2013. Unmanned aerial vehicles (UAVs) for surveying marine fauna: A dugong case study. PLoS ONE, 8 : e79556. https://doi.org/10.1371/journal.pone.0079556.
10.1371/journal.pone.0079556 Google Scholar
Hodgson, J.C. et L.P. Koh, 2016. Best practice for minimising unmanned aerial vehicle disturbance to wildlife in biological field research. Current Biology, 26 : R404-R405. https://doi.org/10.1016/j.cub.2016.04.001.
10.1016/j.cub.2016.04.001 Google Scholar
Hodgson, J.C., S.M. Baylis, R. Mott, A. Herrold et R.H. Clarke, 2016. Precision wildlife monitoring using unmanned aerial vehicles. Scientific Reports, 6 : 22574. https://doi.org/10.1038/srep22574.
10.1038/srep22574 Google Scholar
Hodgson, J.C., R. Mott, S.M. Baylis, T.T. Pham, S. Wotherspoon, A.D. Kilpatrick, R.R. Segaran, I. Reid, A. Therauds et L.P. Koh, 2018. Drones count wildlife more accurately and precisely than humans. Methods in Ecology and Evolution, 9 : 1160-1167. https://doi.org/10.1111/2041-210X.12974.
10.1111/2041-210X.12974 Google Scholar
Hu, J.B., X.M. Wu et M.X. Dai, 2020. Estimating the population size of migrating Tibetan antelopes Pantholops hodgsonii with unmanned aerial vehicles. Oryx, 54 (1) : 101-109. https://doi.org/10.1017/S0030605317001673.
10.1017/S0030605317001673 Google Scholar
Hyun, C.-U., M. Park et W.Y. Lee, 2020. Remotely piloted aircraft system (RPAS)-based wildlife detection: A review and case studies in maritime Antartica. Animals, 10 : 2387. https://doi.org/10.3390/ani10122387.
10.3390/ani10122387 Google Scholar
Inoue, S., S. Yamamoto, M. Ringhofer, R.S. Mendonça, C. Pereira et S. Hirata, 2019. Spatial positioning of individuals in a group of feral horses: A case study using drone technology. Mammal Research, 64 (2) : 249-263. https://doi.org/10.1007/s13364-019-00434-5.
10.1007/s13364-018-0400-2 Google Scholar
Inoue, S., S. Yamamoto, M. Ringhofer, R.S. Mendonça et S. Hirata, 2020. Lateral position preference in grazing feral horses. Ethology, 126 : 111-119. https://doi.org/10.1111/eth.12966.
10.1111/eth.12966 Google Scholar
Israel, M., 2011. A UAV-based roe deer fawn detection system. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38 : 1-5. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-51-2011.
10.5194/isprsarchives-XXXVIII-1-C22-51-2011 Google Scholar
Ivošević, B., Y.-G. Han et O. Kwon, 2017. Monitoring butterflies with an unmanned aerial vehicle: Current possibilities and future potentials. Journal of Ecology and Environment, 41 : 12. https://doi.org/10.1186/s41610-017-0028-1.
10.1186/s41610-017-0028-1 Google Scholar
Jewell, Z., 2013. Effect of monitoring technique on quality of conservation science. Conservation Biology, 27 : 501-508. https://doi.org/10.1111/cobi.12066.
10.1111/cobi.12066 Google Scholar
Jewitt, D., 2018. The use of drones in conservation. Position IT, (Aug/Sep) : 20-23.
10.5194/isprsarchives-XL-3-W3-355-2015 Google Scholar
Johnston, D.W., 2019. Unoccupied aircraft systems in marine science and conservation. Annual Review of Marine Science, 11 : 439-463. https://doi.org/10.1146/annurev-marine-010318-095323.
10.1146/annurev-marine-010318-095323 Google Scholar
Jones IV, G.P., L.G. Pearlstine et H.F. Percival, 2006. An assessment of small unmanned aerial vehicles for wildlife research. Wildlife Society Bulletin, 34 : 750-758.
10.2193/0091-7648(2006)34[750:AAOSUA]2.0.CO;2 Google Scholar
Junda, J., E. Greene et D.M. Bird, 2015. Proper flight technique for using a small rotary-winged drone aircraft to safely, quickly, and accurately survey raptor nests. Journal of Unmanned Vehicle Systems, 3 : 222-236. http://dx.doi.org/10.1139/juvs-2015-0003.
10.1139/juvs-2015-0003 Google Scholar
Junda, J.H., E. Greene, D. Zazelenchuk et D.M. Bird, 2016. Nest defense behaviour of four raptor species (osprey, bald eagle, ferruginous hawk, and red-tailed hawk) to a novel aerial intruder—A small rotary-winged drone. Journal of Unmanned Vehicle Systems, 4 : 217-227. http://doi.org/10.1139/juvs-2016-0004.
10.1139/juvs-2016-0004 Google Scholar
Kelaher, B.P., A.P. Colefax, A. Tagliafico, M.J. Bishop, A. Giles et P.A. Butcher, 2019. Assessing variation in assemblages of large marine fauna off ocean beaches using drones. Marine and Freshwater Research, 71 (1) : 68. https://doi.org/10.1071/MF18375.
10.1071/MF18375 Google Scholar
Kellenberger, B., D. Marcos et D. Tuia, 2018. Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning. Remote Sensing of Environment, 216 : 139-153. https://doi.org/10.1016/j.rse.2018.06.028.
10.1016/j.rse.2018.06.028 Google Scholar
Kim, H.G., J.-S. Park et D.-H. Lee, 2018. Potential of unmanned aerial sampling for monitoring insect populations in rice fields. Florida Entomologist, 101 (2) : 330-334. https://doi.org/10.1653/024.101.0229.
10.1653/024.101.0229 Google Scholar
Kiszka, J.J., J. Mourier, K. Gastrich et M.R. Heithaus, 2016. Using unmanned aerial vehicles (UAVs) to investigate shark and ray densities in a shallow coral lagoon. Marine Ecology Progress Series, 560 : 237-242. https://doi.org/10.3354/meps11945.
10.3354/meps11945 Google Scholar
Koski, W.R., T. Allen, D. Ireland, G. Buck, P.R. Smith, A.M. Macrander, M.A. Halick, C. Rushing, D.J. Sliwa et T.L. McDonald, 2009. Evaluation of an unmanned airborne system for monitoring marine mammals. Aquatic Mammals, 35 (3) : 347-357. https://doi.org/10.1578/AM.35.3.2009.347.
10.1578/AM.35.3.2009.347 Google Scholar
Koski, W.R., G. Gamage, A.R. Davis, T. Mathews, B. LeBlanc et S.H. Ferguson, 2015. Evaluation of UAS for photographic re-identification of bowhead whales, Balaena mysticetus. Journal of Unmanned Vehicle Systems, 3 : 22-29. http://dx.doi.org/10.1139/juvs-2014-0014.
10.1139/juvs-2014-0014 Google Scholar
Krause, D.J., J.T. Hinke, W.L. Perryman, M.E. Goebel et D.J. LeRoi, 2017. An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system. PLoS ONE, 12 (11) : e0187465. https://doi.org/10.1371/journal.pone.0187465.
10.1371/journal.pone.0187465 Google Scholar
Kudo, H., Y. Koshino, A. Eto, M. Ichimura et M. Kaeriyama, 2012. Cost-effective accurate estimates of adult chum salmon, Oncorhynchus keta, abundance in a Japanese river using a radio-controlled helicopter. Fisheries Research, 119 : 94-98. https://doi.org/10.1016/j.fishres.2011.12.010.
10.1016/j.fishres.2011.12.010 Google Scholar
Laporte, P., 2019. La technologie au service de la science ! Société Provancher. Disponible en ligne à : https://www.provancher.org/infolettres/utilisation-dun-drone-pour-linventaire-de-la-heronniere-de-lile-aux-basques/ [Visité le 2021-04-15].
10.2478/eje-2018-0012 Google Scholar
Levy, J., C. Hunter, T. Lukacazyk et E.C. Franklin, 2018. Assessing the spatial distribution of coral bleaching using small unmanned aerial systems. Coral Reefs, 37 : 373-387. https://doi.org/10.1007/s00338-018-1662-5.
10.1007/s00338-018-1662-5 Google Scholar
Lhoest, S., J. Linchant, S. Quevauvillers, C. Vermeulen et P. Lejeune, 2015. How many hippos (HOMHIP): Algorithm for automatic counts of animals with infra-red thermal imagery from UAV. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 40 : 355-362. https://doi.org/10.5194/isprsarchives-XL-3-W3-355-2015.
10.5194/isprsarchives-XL-3-W3-355-2015 Google Scholar
Linchant, J., J. Lisein, J. Semeki, P. Lejeune et C. Vermeulen, 2015. Are unmanned aircraft systems (UASs) the future of wildlife monitoring? A review of accomplishments and challenges. Mammal Review, 45 : 239-252. https://doi.org/10.1111/mam.12046.
10.1111/mam.12046 Google Scholar
Löcken, H., O.W. Fischer, J. Selz et M. Boppré, 2020. ‘Drone-Netting’ for sampling live insects. Journal of Insect Science, 20 (5) : 1-3. https://doi.org/10.1093/jisesa/ieaa086.
10.1093/jisesa/ieaa086 Google Scholar
López, J.J. et M. Mulero-Pázmány, 2019. Drones for conservation in protected areas: Present and future. Drones, 3 (10) : doi:10.3390. https://doi.org/10.3390/drones3010010.
10.3390/drones3010010 Google Scholar
Lyons, M., K. Brandis, C. Callaghan, J. McCann, C. Mills, S. Ryall et R. Kingsford, 2018. Bird interactions with drones, from individuals to large colonies. Australian Field Ornithology, 35 : 51-56. http://dx.doi.org/10.20938/afo35051056.
10.20938/afo35051056 Google Scholar
Mallory, M.L., C.J. Dey, J. McIntyre, I. Pratte, C.L. Mallory, C.M. Francis, A.L. Black, C. Geoffroy, R. Dickson et J.F. Provencher, 2020. Long-term declines in the size of northern fulmar (Fulmarus glacialis) colonies on Eastern Baffin Island, Canada. Arctic, 73 (2) : 187-194. https://doi.org/10.14430/arctic70290.
10.14430/arctic70290 Google Scholar
McClelland, G.T.W., A.L. Bond, A. Sardana et T. Glass, 2016. Rapid population estimate of a surface-nesting seabird on a remote island using a low-cost unmanned aerial vehicle. Marine Ornithology, 44 : 215-220.
10.1139/juvs-2015-0006 Google Scholar
McEvoy, J.F., G.P. Hall et P.G. McDonald, 2016. Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: Disturbance effects and species recognition. PeerJ, 4 : e1831. https://doi.org/10.7717/peerj.1831.
10.7717/peerj.1831 Google Scholar
McKellar, A.E., N.G. Shephard et D. Chabot, 2020. Dual visible-thermal camera approach facilitates drone surveys of colonial marshbirds. Remote Sensing in Ecology and Conservation, 7 (2) : 214-226. https://doi.org/10.1002/rse2.183.
10.1002/rse2.183 Google Scholar
[MFFP] Ministère des Forêts, de la Faune et des Parcs, 2021a. Protocole standardisé pour le suivi de la nidification et de la productivité du faucon pèlerin au Québec. Gouvernement du Québec, Québec. 20 p. + annexes. Disponible en ligne à : https://mffp.gouv.qc.ca/documents/faune/PT_standardise_suivi_nidification_productivite_faucon_pelerin.pdf [Visité le 9 juillet 2021].
10.1111/jfb.13645 Google Scholar
[MFFP] Ministère des Forêts, de la Faune et des Parcs, 2021b. Protocole standardisé pour le suivi de la nidification et de la productivité de l’aigle royal au Québec. Gouvernement du Québec, Québec. 24 p. + annexes. Disponible en ligne à : https://mffp.gouv.qc.ca/documents/faune/PT_standardise_suivi_nidification_productivite_aigle_royal.pdf [Visité le 9 juillet 2021].
10.2981/wlb.00679 Google Scholar
Moreland, E.E., M.F. Cameron, R.P. Angliss et P.L. Boveng, 2015. Evaluation of a ship-based unoccupied aircraft system (UAS) for surveys of spotted and ribbon seals in the Bering Sea pack ice. Journal of Unmanned Vehicle Systems, 3 : 114-122. http://dx.doi.org/10.1139/juvs-2015-0012.
10.1139/juvs-2015-0012 Google Scholar
Mulero-Pázmány, M., R. Stolper, L.D. van Essen, J.J. Negro et T. Sassen, 2014. Remotely piloted aircraft systems as a rhinoceros anti-poaching tool in Africa. PLoS ONE, 9 (1) : e83873. https://doi.org/10.1371/journal.pone.0083873.
10.1371/journal.pone.0083873 Google Scholar
Mulero-Pázmány, M., S. Jenni-Eiermann, N. Strebel, T. Sattler, J.J. Negro et Z. Tablado, 2017. Unmanned aircraft systems as a new source of disturbance for wildlife: A systematic review. PLoS ONE, 12 (6) : e0178448. https://doi.org/10.1371/journal.pone.0178448.
10.1371/journal.pone.0178448 Google Scholar
Nazir, S. et M. Kaleem, 2021. Advances in image acquisition and processing technologies transforming animal ecological studies. Ecological Informatics, 61 : 101212. https://doi.org/10.1016/j.ecoinf.2021.101212.
10.1016/j.ecoinf.2021.101212 Google Scholar
Ngabinzeke, J.S., J. Linchant, S. Quevauvillers, J.-M. KahindoMuhongya, P. Lejeune et C. Vermeulen, 2016. Potentiel des véhicules aériens sans pilote dans la détection des activités humaines illégales dans les aires protégées en République Démocratique du Congo. Journal of Unmanned Vehicle Systems, 4 : 151-159. http://dx.doi.org/10.1139/juvs-2015-0035.
10.1139/juvs-2015-0035 Google Scholar
[NOAA] National Oceanic and Atmospheric Administration, 2014. Unmanned aerial vehicle offers a new view of killer whales. Disponible en ligne à : https://videos.fisheries.noaa.gov/detail/videos/west-coast-region/video/3812337968001/unmanned-aerial-vehicle-offers-a-new-view-of-killer- whales?autoStart=true&page=1. [Visité le 2021-04-15].
10.1002/wsb.700 Google Scholar
[NOAA] National Oceanic and Atmospheric Administration, 2017. Beluga whale hexacopter survey. Disponible en ligne à : https://www.fisheries.noaa.gov/taxonomy/term/1000008786. [Visité le 2021-04-15].
10.1159/000496971 Google Scholar
Nowak, M.M., K. Dziób et P. Bogawski, 2018. Unmanned aerial vehicles (UAVs) in environmental biology: A review. European Journal of Ecology, 4 (2) : 56-74.
10.2478/eje-2018-0012 Google Scholar
Oosthuizen, W.C., L. Krüger, W. Jouanneau et A.D. Lowther, 2020. Unmanned aerial vehicle (UAV) survey of the Antarctic shag (Leucocarbo Bransfieldensis) breeding colony at Harmony Point, Nelson Island, South Shetland Islands. Polar Biology, 43 (2) : 187-191. https://doi.org/10.1007/s00300-019-02616-y.
10.1007/s00300-019-02616-y Google Scholar
Otero, V., R. Van De Kerchove, B. Satyanarayana, C. Martínez-Espinosa, M.A. Bin Fisol, M.R. Bin Ibrahim, I. Sulong, H. Mohd-Lokman, R. Lucas et F. Dahdouh-Guebas, 2018. Managing mangrove forests from the sky: Forest inventory using field data and unmanned aerial vehicle (UAV) imagery in the Matang Mangrove Forest Reserve, Peninsular Malaysia. Forest Ecology and Management, 411 : 35-45. https://doi.org/10.1016/j.foreco.2017.12.049.
10.1016/j.foreco.2017.12.049 Google Scholar
Ott, M.C., 2020. Using unmanned aerial systems (drones) with a thermal sensor to map and count deer population. Williams Honors College, Honors Research Projects, 1068, 27 p.
10.1139/juvs-2017-0026 Google Scholar
Pimm, S.L., S. Alibhai, R. Bergl, A. Dehgan, C. Giri, Z. Jewell, L. Joppa, R. Kays et S. Loarie, 2015. Emerging technologies to conserve biodiversity. Trends in Ecology and Evolution, 30 : 685-696. https://doi.org/10.1016/j.tree.2015.08.008.
10.1016/j.tree.2015.08.008 Google Scholar
Potapov, E.R., I.G. Utekhina, M.J. McGrady et D. Rimlinger, 2013. Usage of UAV for surveying Steller’s sea eagle nests. Raptors Conservation, 27 : 253-260.
10.1002/ajp.22446 Google Scholar
Prosekov, A., A. Kuznetsov, A. Rada et S. Ivanova, 2020. Methods for monitoring large terrestrial animals in the wild. Forests, 11 : 808. https://doi.org/10.3390/f11080808.
10.3390/f11080808 Google Scholar
Provost, E.J., P.A. Butcher, M.A. Coleman, D. Bloom et B.P. Kelaher, 2020. Aerial drone technology can assist compliance of trap fisheries. Fisheries Management and Ecology, 27 (4) : 381-388. https://doi.org/10.1111/fme.12420.
10.1111/fme.12420 Google Scholar
Puttock, A.K., A.M. Cunliffe, K. Anderson et R.E. Brazier, 2015. Aerial photography collected with a multirotor drone reveals impact of Eurasian beaver reintroduction on ecosystem structure. Journal of Unmanned Vehicle Systems, 3 (3) : 123-130. https://doi.org/10.1139/juvs-2015-0005.
10.1139/juvs-2015-0005 Google Scholar
Rango, A., A. Laliberte, C. Steele, J.E. Herrick, B. Bestelmeyer, T. Schmugge, A. Roanhorse et V. Jenkins, 2006. Using unmanned aerial vehicles for rangelands: Current applications and future potentials. Environmental Practice, 8 : 159-168. https://doi.org/10.1017/S1466046606060224.
10.1017/S1466046606060224 Google Scholar
Ratcliffe, N., D. Guihen, J. Robst, S. Crofts, A, Stanworth et P. Enderlein, 2015. A protocol for the aerial survey of penguin colonies using UAVs. Journal of Unmanned Vehicle Systems, 3 (3) : 96-101. https://doi.org/10.1139/juvs-2015-0006.
10.1139/juvs-2015-0006 Google Scholar
Rebolo-Ifrán, N., M. Graña Grilli et S.A. Lambertucci, 2019. Drones as a threat to wildlife: YouTube complements science in providing evidence about their effect. Environmental Conservation. https://doi.org/10.1017/S0376892919000080.
10.1017/S0376892919000080 Google Scholar
Rees, A.F., L. Avens, K. Ballorain, E. Bevan, A.C. Broderick, R.R. Carthy, M.J.A. Christianen, G. Duclos, M.R. Heithaus, D.W. Johnston, J.C. Mangel, F. Paladino, K. Pendoley, R.D. Reina, N.J. Robinson, R. Ryan, S.T. Sykora-Bodie, D. Tilley, M.R. Varela, E.R. Whitman, P.A. Whittock, T. Wibbels et B.J.Godley, 2018. The potential of unmanned aerial systems for sea turtle research and conservation: A review and future directions. Endangered Species Research, 35 : 81-100. https://doi.org/10.3354/esr00877.
10.3354/esr00877 Google Scholar
Rieucau, G., J.J. Kiszka, J.C. Castillo, J. Mourier, K.M. Boswell et M.R. Heithaus, 2018. Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: A case study on reef sharks Carcharhinus melanopterus shoaling behaviour. Journal of Fish Biology, 93 : 119-127. https://doi.org/10.1111/jfb.13645.
10.1111/jfb.13645 Google Scholar
Rischette, A.C., T.J. Hovick, R.D. Elmore et B.A. Geaumont, 2020. Use of small unmanned aerial systems for sharp-tailed grouse lek surveys. Wildlife Biology. https://doi.org/10.2981/wlb.00679.
10.2981/wlb.00679 Google Scholar
Rodríguez, A., J.J. Negro, M. Mulero, C. Rodríguez, J. Hernández-Pliego et J. Bustamante, 2012. The eye in the sky: Combined use of unmanned aerial systems and GPS data loggers for ecological research and conservation of small birds. PLoS ONE, 7 (12) : e50336. https://doi.org/10.1371/journal.pone.0050336.
10.1371/journal.pone.0050336 Google Scholar
Rovero, F. et F. Zimmermann, 2016. Camera trapping for wildlife research. Pelagic Publishing, Exeter, UK, 320 p.
10.1093/oso/9780198787617.001.0001 Google Scholar
Sardà-Palomera, F., G. Bota, C.Viñolo, O. Pallarés, V. Sazatornil, L. Brotons, S. Gomáriz et F. Sardà, 2012. Fine-scale bird monitoring from light unmanned aircraft systems. Ibis, 154 : 177-183. https://doi.org/10.1111/j.1474-919X.2011.01177.x.
10.1111/j.1474-919X.2011.01177.x Google Scholar
Sasse, D.B., 2003. Job-related mortality of wildlife workers in the United States, 1937-2000. Wildlife Society Bulletin, 31 : 1015-1020.
10.1016/S0001-4575(02)00037-4 Google Scholar
Schaub, J., B.P.V. Hunt, E.A. Pakhomov, K. Holmes, Y. Lu et L. Quayle, 2018. Using unmanned aerial vehicles (UAVs) to measure jellyfish aggregations. Marine Ecology Progress Series, 591 : 29-36. https://doi.org/10.3354/meps12414.
10.3354/meps12414 Google Scholar
Schofield, G., K. Papafitsoros, R. Haughey et K. Katselidis, 2017. Aerial and underwater surveys reveal temporal variation in cleaning-station use by sea turtles at a temperate breeding area. Marine Ecology Progress Series, 575 : 153-164. https://doi.org/10.3354/meps12193.
10.3354/meps12193 Google Scholar
Scholten, B.D., A.R. Beard, H. Choi, D.M. Baker, M.E. Caulfield et D.S. Proppe, 2020. Short-term exposure to unmanned aerial vehicles does not alter stress responses in breeding tree swallows. Conservation Physiology, 8 (1) : coaa080. https://doi.org/10.1093/conphys/coaa080.
10.1093/conphys/coaa080 Google Scholar
Scobie, C.A. et C.H. Hugenholtz, 2016. Wildlife monitoring with unmanned aerial vehicles: Quantifying distance to auditory detection. Wildlife Society Bulletin, 40 (4) : 781-785. https://doi.org/10.1002/wsb.700.
10.1002/wsb.700 Google Scholar
Semel, B.P., S.M. Karpanty, F.F. Vololonirina et A.N. Rakotonanahary, 2020. Eyes in the sky: Assessing the feasibility of low-cost, ready-to-use unmanned aerial vehicles to monitor primate populations directly. Folia Primatologica, 91 (1) : 69-82. https://doi.org/10.1159/000496971.
10.1159/000496971 Google Scholar
Seymour, A.C., J. Dale, M. Hammill, P.N. Halpin et D.W. Johnston, 2017. Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery. Scientific Reports, 7 : 45127. https://doi.org/10.1038/srep45127.
10.1038/srep45127 Google Scholar
Silvy, N.J. (édit.), 2012. The wildlife techniques manual—Research (Vol. 1). 7e édition. The Johns Hopkins University Press, Baltimore, MD, 686 p.
Google Scholar
[Sépaq] Société des établissements de plein air du Québec, 2020. Utilisation des drones. Disponible en ligne à : https://www.sepaq.com/annexes/quoi-faire/utilisation-drones.dot?language_id=2. [Visité le 2021-07-09].
Google Scholar
Stark, D.J., I.P. Vaughan, L.J. Evans, H. Kler et B. Goossens, 2017. Combining drones and satellite tracking as an effective tool for informing policy change in riparian habitats: A proboscis monkey case study. Remote Sensing in Ecology and Conservation, 4 (1) : 44-52. https://doi.org/10.1002/rse2.51.
10.1002/rse2.51 Google Scholar
Sun, T., S. Yi, F. Hou, D. Luo, J. Hu et Z. Zhou, 2020. Quantifying the dynamics of livestock distribution by unmanned aerial vehicles (UAVs): A case study of yak grazing at the household scale. Rangeland Ecology and Management, 73 : 642-648. https://doi.org/10.1016/j.rama.2020.05.004.
10.1016/j.rama.2020.05.004 Google Scholar
Thapa, G.J., K. Thapa, R. Thapa, S.R. Jnawali, S.A. Wich, L.P. Poudyal et S. Karki, 2018. Counting crocodiles from the sky: Monitoring the critically endangered gharial (Gavialis gangeticus) population with an unmanned aerial vehicle (UAV). Journal of Unmanned Vehicle Systems, 6 : 71-82. https://doi.org/10.1139/juvs-2017-0026.
10.1139/juvs-2017-0026 Google Scholar
The Ornithological Council, 2018. Guidelines to the use of wild birds in—2018 Supplement—Summary of literature reporting use of drones to study birds. Washington, D.C., 14 p.
Google Scholar
Tyler, S., O.P. Jensen, Z. Hogan, S. Chandra, L.M. Galland et J. Simmons, 2018. Perspectives on the application of unmanned aircraft for freshwater fisheries census. Fisheries, 43 (11) : 510-516. https://doi.org/10.1002/FSH.10167.
10.1002/fsh.10167 Google Scholar
van Andel, A.C., S.A. Wich, C. Boesch, L.P. Koh, M.M. Robbins, J. Kelly et H.S. Kuehl, 2015. Locating chimpanzee nests and identifying fruiting trees with an unmanned aerial vehicle. American Journal of Primatology, 77 : 1122-1134. https://doi.org/10.1002/ajp.22446.
10.1002/ajp.22446 Google Scholar
van Gemert, J.C., C.R. Verschoor, P. Mettes, K. Epema, L.P. Koh et S. Wich, 2014. Nature conservation drones for automatic localization and counting of animals. Dans : Agapito, L., M.M. Bronstein et C. Rother (édit.). Lecture notes in computer science. Vol. 8925, Intelligent Sensory Information Systems, Springer, New York, p. 255-270.
10.1007/978-3-319-16178-5_17 Google Scholar
Vas, E., A. Lescroël, O. Duriez, G. Boguszewski et D. Grémillet, 2015. Approaching birds with drones: First experiments and ethical guidelines. Biology Letters, 11 (2) : 20140754. http://dx.doi.org/10.1098/rsbl.2014.0754.
10.1098/rsbl.2014.0754 Google Scholar
Vermeulen, C., P. Lejeune, J. Lisein, P. Sawadogo et P. Bouché, 2013. Unmanned aerial survey of elephants. PLoS ONE, 8 (2) : e54700. https://doi.org/10.1371/journal.pone.0054700.
10.1371/journal.pone.0054700 Google Scholar
Wallace, P., R. Martin et I. White, 2018. Keeping pace with technology: Drones, disturbance and policy deficiency. Journal of Environmental Planning and Management, 61 (7) : 1271-1288. https://doi.org/10.1080/09640568.2017.1353957.
10.1080/09640568.2017.1353957 Google Scholar
Wang, D.L., Q.Q. Shao et H.Y. Yue, 2019. Surveying wild animals from satellites, manned aircraft and unmanned aerial systems (UASs): A review. Remote Sensing, 11 (11) : 1308. https://doi.org/10.3390/rs11111308.
10.3390/rs11111308 Google Scholar
Wang, Y., Z. Lu, Y. Sheng et Y. Zhou, 2020. Remote sensing applications in monitoring of protected areas. Remote Sensing, 12 (9) : 1370. https://doi.org/10.3390/rs12091370.
10.3390/rs12091370 Google Scholar
Watts, A.C., J.H. Perry, S.E. Smith, M.A. Burgess, B.E. Wilkinson, Z. Szantoi, P.G. Ifju et H.F. Percival, 2010. Small unmanned aircraft systems for low-altitude aerial surveys. Journal of Wildlife Management, 74 (7) : 1614-1619. https://doi.org/10.2193/2009-425.
10.1111/j.1937-2817.2010.tb01292.x Google Scholar
Weissensteiner, M.H., J.W. Poelstra et J.B.W. Wolf, 2015. Low-budget ready-to-fly unmanned aerial vehicles: An effective tool for evaluating the nesting status of canopy-breeding bird species. Journal of Avian Biology, 46 (4) : 425-430. https://doi.org/10.1111/jav.00619.
10.1111/jav.00619 Google Scholar
White, C.M., N.J. Clum, T.J. Cade et W.G. Hunt, 2002. Peregrine falcon (Falco peregrinus), version 2.0. Dans : Poole, A.F. et F.B. Gill (édit.). The Birds of North America. Cornell Lab of Ornithology, Ithaca, NY, États-Unis. https://doi.org/10.2173/bna.660.
10.2173/bna.perfal.02 Google Scholar
Whitehead, K., C.H. Hugenholtz, S. Myshak, O. Brown, A. LeClair, A. Tamminga, T. E. Barchyn, B. Moorman et B. Eaton, 2014. Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: Scientific and commercial applications. Journal of Unmanned Vehicle Systems, 2 : 86-102. http://dx.doi.org/10.1139/juvs-2014-0007.
10.1139/juvs-2014-0007 Google Scholar
Wich, S.A. et L.P. Koh, 2018. Conservation drones: Mapping and monitoring biodiversity. Oxford University Press, Oxford, 118 p. http://doi.org/10.1093/oso/9780198787617.001.0001.
10.1093/oso/9780198787617.001.0001 Google Scholar
Wich, S., D. Dellatore, M. Houghton, R. Ardi et L.P. Koh, 2016. A preliminary assessment of using conservation drones for Sumatran orang-utan (Pongo abelii) distribution and density. Journal of Unmanned Vehicle Systems, 4 : 45-52. http://dx.doi.org/10.1139/juvs-2015-0015.
10.1139/juvs-2015-0015 Google Scholar
Wiegmann, D.A. et N. Taneja, 2003. Analysis of injuries among pilots involved in fatal general aviation airplane accidents. Accident Analysis and Prevention, 35 : 571–577. https://doi.org/10.1016/s0001-4575(02)00037-4.
10.1016/S0001-4575(02)00037-4 Google Scholar
Wilson, D.E., F.R. Cole, J.D. Nichols, R. Rudran et M.S. Foster (édit.), 1996. Measuring and monitoring biological diversity—Standard methods for mammals. Smithsonian Institution Press, Washington, D.C., 409 p.
Google Scholar
Witczuk, J., S. Pagacz, A. Zmarz et M. Cypel, 2017. Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests—Preliminary results. International Journal of Remote Sensing, 39 (15-16) : 5504-5521. https://doi.org/10.1080/01431161.2017.1390621.
10.1080/01431161.2017.1390621 Google Scholar
Xu, B., W. Wang, G. Falzon, P. Kwan, L. Guo, G. Chen, A. Tait et D. Schneider, 2020. Automated cattle counting using Mask R-CNN in quadcopter vision system. Computers and Electronics in Agriculture, 171 : 105300. https://doi.org/10.1016/j.compag.2020.105300.
10.1016/j.compag.2020.105300 Google Scholar
Zhang, H., C. Wang, S. T. Turvey, Z. Sun, Z. Tan, Q. Yang, W. Long, X. Wu et D. Yang, 2020. Thermal infrared imaging from drones can detect individuals and nocturnal behavior of the world’s rarest primate. Global Ecology and Conservation, 23 : e01101. https://doi.org/10.1016/j.gecco.2020.e01101.
10.1016/j.gecco.2020.e01101 Google Scholar