Skip to main content Accessibility help

ENVIRONMENTAL REVIEWS AND CASE STUDIES: Applications of Unmanned Aircraft Systems (UAS) for Waterbird Surveys

  • Sharon Dulava (a1), William T. Bean (a2) and Orien M. W. Richmond (a3)


Utilizing unmanned aircraft systems (UAS) can be an efficient and repeatable means of surveying wildlife, especially waterbirds. As with any technology in its infancy, case studies offer opportunities to explore drawbacks and limitations, both anticipated and unanticipated. We examined the relationship between flight altitude and camera focal length on bird identification. We then conducted a post-hoc analysis to examine the effect of flight altitude on bird flushing behavior. We flew UAS missions at three locations in California and Nevada to assess the use of UAS for censusing non-nesting waterbirds. A minimum pixel resolution of approximately 5 mm was needed be able to identify most waterbird species from imagery. Sensors needed to be carefully calibrated in order to obtain images of sufficient quality to identify waterbirds over open water. Our results suggest that gas-powered UAS may result in increased rates of flushing at low flight altitudes for some waterbirds. With careful design of surveys and processing workflow, UAS show promise for censusing and monitoring waterbirds.

Environmental Practice 17: 201–210 (2015)


Corresponding author

*Address correspondence to: Sharon Dulava, Humboldt State University, 1 Harpst St., Arcata, CA 95521; (phone) 925-285-9473; (fax) 707-826-4060; (e-mail)


Hide All
Bajzak, D., and Piatt, J.F.. 1990. Computer-Aided Procedure for Counting Waterfowl on Aerial Photographs. Wildlife Society Bulletin 18:125129.
Bakó, G., Tolnai, M., and Takács, Á.. 2014. Introduction and Testing of a Monitoring and Colony-Mapping Method for Waterbird Populations that Uses High-Speed and Ultra-Detailed Aerial Remote Sensing. Sensors 14(7):1282812846.
Bartholomew, G.A. 1942. The Fishing Activities of Double-Crested Cormorants on San Francisco Bay. Condor, 1321.
Bartmann, R.M., White, G.C., Carpenter, L.H., and Garrott, R.A.. 1987. Aerial Mark-Recapture Estimates of Confined Mule Deer in Pinyon-Juniper Woodland. The Journal of Wildlife Management 51(1):4146.
Brown, A.L. 1990. Measuring the Effect of Aircraft Noise on Seabirds. Environment International 16(4-6):587592.
Burnham, K.P., and Anderson, D.R.. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, (Second Edition). Springer-Verlag, Medford, MA, 351pp.
Caughley, G. 1974. Bias in Aerial Survey. The Journal of Wildlife Management 38(4):921933.
Chabot, D., and Bird, D.. 2012. Evaluation of an Off-the-Shelf Unmanned Aircraft System for Surveying Flocks of Geese. Waterbirds 35(1):170174.
Conomy, J.T., Collazo, J.A., Dubovsky, J.A., and Fleming, W. J.. 1998. Dabbling Duck Behavior and Aircraft Activity in Coastal North Carolina. The Journal of Wildlife Management 62(3):11271134.
Freddy, D.J., White, G.C., Kneeland, M.C., Kahn, R.H., Unsworth, J.W., deVergie, W.J., Graham, V.K., Ellenberger, J.H., and Wagner, C.H.. 2004. How Many Mule Deer Are There? Challenges of Credibility in Colorado. Wildlife Society Bulletin 32(3):916927.
Frederick, P.C., Hylton, B., Heath, J.A., and Ruane, M.. 2003. Accuracy and Variation in Estimates of Large Numbers of Birds by Individual Observers Using an Aerial Survey Simulator. Journal of Field Ornithology 74(3):281287.
Groom, G., Stjernholm, M., Nielsen, R.D., Fleetwood, A., and Petersen, I.K.. 2013. Remote Sensing Image Data and Automated Analysis to Describe Marine Bird Distributions and Abundances. Ecological Informatics 14:28.
Hedley, J.D., Harborne, A.R., and Mumby, P.J.. 2005. Technical Note: Simple and Robust Removal of Sun Glint for Mapping Shallow-Water Benthos. International Journal of Remote Sensing 26(10):21072112.
Jones, G.P., Pearlstine, L.G., and Percival, H.F.. 2006. An Assessment of Small Unmanned Aerial Vehicles for Wildlife Research. Wildlife Society Bulletin 34(3):750758.
Kay, S., Hedley, J.D., and Lavender, S.. 2009. Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: A Review of Methods for Visible and Near-Infrared Wavelengths. Remote Sensing 1(4):697730.
Koh, L.P., and Wich, S.A.. 2012. Dawn of Drone Ecology: Low-Cost Autonomous Aerial Vehicles for Conservation. Tropical Conservation Science 5(2):121132.
Komenda-Zehnder, S., Cevallos, M., and Bruderer, B.. 2003. Effects of Disturbance by Aircraft Overflight on Waterbirds: An Experimental Approach, IBSC26/WP-LE2. International Bird Strike Committee, 13pp. Available at
Laliberte, A., and Ripple, W.. 2003. Automated Wildlife Counts from Remotely Sensed Imagery. Wildlife Society Bulletin 31:362371.
Lawrence, G.E. 1950. The Diving and Feeding Activity of the Western Grebe on the Breeding Grounds. Condor, 316.
Office of Aviation Services. 2014. 25th Annual Aviation Safety Summary & Annual Report FY 2014. Available at
R Core Team. 2014. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Available at
Reeves, H.M. 1984. Portraits - Frederick C. Lincoln. In Flyways: Pioneering Waterfowl Management in North America, A.S. Hawkins, R.C. Hanson, H.K. Nelson and H.M. Reeves, eds. United States Fish & Wildlife Service, Washington, DC, 7274.
Sardà-Palomera, F., Bota, G., Viñolo, C., Pallarés, O., Sazatornil, V., Brotons, L., Gomáriz, S., and Sardà, F.. 2012. Fine-Scale Bird Monitoring from Light Unmanned Aircraft Systems. Ibis 154(1):177183.
Sasse, D.B. 2003. Job-Related Mortality of Wildlife Workers in the United States, 1937-2000. Wildlife Society Bulletin 31(4):10151020.
Terletzky, P., Ramsey, R.D., and Neale, C.M.U.. 2012. Spectral Characteristics of Domestic and Wild Mammals. GIScience and Remote Sensing 49(4):597608.
Vas, E., Lescroël, A., Duriez, O., Boguszewski, G., and Grémillet, D.. 2015. Approaching Birds with Drones: First Experiments and Ethical Guidelines. Biology Letters 11(2) DOI: 10.1098/rsbl.2014.0754.
Venables, W.N., and Ripley, B.D.. 2002. Modern Applied Statistics with S, (Fourth Edition). Springer, New York, NY, 330pp.
Watts, A.C., Ambrosia, V.G., and Hinkley, E.A.. 2012. Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use. Remote Sensing 4(6):16711692.
White, G.C., Bartmann, R.M., Carpenter, L.H., and Garrott, R.A.. 1989. Evaluation of Aerial Line Transects for Estimating Mule Deer Densities. The Journal of Wildlife Management 53(3):625635.
Yee, T.W. 2010. The VGAM Package for Categorical Data Analysis. Journal of Statistical Software 32(10):134.


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed