Estimating kangaroo density by aerial survey: a comparison of thermal cameras with human observers
Mark Lethbridge
A C , Michael Stead B and Cameron Wells B
+ Author Affiliations
- Author Affiliations
A Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia.
B EcoKnowledge, PO Box 632, Mylor, SA 5153, Australia.
C Corresponding author. Email: mark.lethbridge@flinders.edu.au
Wildlife Research 46(8) 639-648 https://doi.org/10.1071/WR18122
Submitted: 16 October 2018 Accepted: 22 June 2019 Published: 23 October 2019
Abstract
Context: Aerial surveys provide valuable information about the population status and distribution of many native and pest vertebrate species. They are vital for evidence-based monitoring, budget planning and setting management targets. Despite aircraft running costs, they remain one of the most cost-effective ways to capture distribution and abundance data over a broad area. In Australia, annual surveys of large macropods are undertaken in several states to inform management, and in some jurisdictions, to help set commercial kangaroo harvest quotas. Improvements in the cost efficiencies of these surveys are continually sought. Aerial thermal imaging techniques are increasingly being tested for wildlife surveys, but to date no studies have directly compared population data derived from thermal imaging with data collected by human observers during the same flight.
Aims: During an aerial survey of western grey kangaroos (Macropus fuliginosus), eastern grey kangaroos (M. giganteus) and red kangaroos (Osphranter rufus) across the state of Victoria, Australia, the objective was to conduct a direct comparison of the effectiveness of thermal camera technology and human observers for estimating kangaroo populations from aerial surveys.
Methods: A thermal camera was mounted alongside an aerial observer on one side of the aircraft for a total of 1360 km of transect lines. All thermal footage was reviewed manually. Population density estimates and distance sampling models were compared with human observer counts.
Key results: Overall, the kangaroo density estimates obtained from the thermal camera data were around 30% higher than estimates derived from aerial observer counts. This difference was greater in wooded habitats. Conversely, human-derived counts were greater in open habitats, possibly due to interference from sunlight and flushing. It was not possible to distinguish between species of macropod in the thermal imagery.
Conclusions: Thermal survey techniques require refining, but the results of the present study suggest that with careful selection of time of day for surveys, more accurate population estimates may be possible than with conventional aerial surveys.
Implications: Conventional aerial surveys may be underestimating animal populations in some habitats. Further studies that directly compare the performance of aerial observers and thermal imaging are required across a range of species and habitats.
Additional keywords: aerial survey, density, harvest, kangaroo, population management, RPA, thermal, UAV.
References
Amos, M., Baxter, G., Finch, N., Lisle, A., and Murray, P. (2014). I just want to count them! Considerations when choosing a deer population monitoring method. Wildlife Biology 20, 362–370.| I just want to count them! Considerations when choosing a deer population monitoring method.Crossref | GoogleScholarGoogle Scholar |
Barthelme, S. (2018). imager: Image processing library based on ‘CImg’, R package version 0.41.1, Available at https://CRAN.R-project.org/package=imager [verified 1 March 2018].
Bayliss, P., and Ligtermoet, E. (2018). Seasonal habitats, decadal trends inabundance and cultural values of magpie geese (Anseranus semipal-mata) on coastal floodplains in the Kakadu Region, northern Australia. Marine and Freshwater Research 69, 1079–1081.
| Seasonal habitats, decadal trends inabundance and cultural values of magpie geese (Anseranus semipal-mata) on coastal floodplains in the Kakadu Region, northern Australia.Crossref | GoogleScholarGoogle Scholar |
Bayliss, P., and Yeomans, K. M. (1989). Distribution and abundance of feral livestock in the ‘Top End’ of the Northern Territory (1985–86), and their relation to population control’ Australian Wildlife Research 16, 651–676.
| Distribution and abundance of feral livestock in the ‘Top End’ of the Northern Territory (1985–86), and their relation to population control’Crossref | GoogleScholarGoogle Scholar |
Bevan, E., Wibbels, T., Najera, B. M. Z., Martinez, M. A. C., Martinez, L. A. S., Martinez, F. I., Cuevas, J. M., Anderson, T., Bonka, A., Hernandez, M. H., Pena, L. J., and Burchfield, P. M. (2015). Unmanned aerial vehicles (UAVs) for monitoring sea turtles in near-shore waters. Marine Turtle Newsletter 145, 19–22.
Brickhill, J. (1985). An aerial survey of nests of malleefowl Leipoa ocellata Gould (Megapodidae) in central New South Wales. Australian Wildlife Research 12, 257–261.
| An aerial survey of nests of malleefowl Leipoa ocellata Gould (Megapodidae) in central New South Wales.Crossref | GoogleScholarGoogle Scholar |
Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., and Thomas, L. (2001). ‘Introduction to Distance Sampling: Estimating Abundance of Biological Populations.’ (Oxford University Press: Oxford, UK.)
Burn, D. M., Udevitz, M. S., Speckman, S. G., and Benter, R. B. (2009). An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery. International Journal of Applied Earth Observation and Geoinformation 11, 324–333.
| An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery.Crossref | GoogleScholarGoogle Scholar |
Butler, D. A., Ballard, W. B., Haskwell, S. B., and Wallace, M. C. (2006). Limitations of thermal infrared imaging for locating neonatal deer in semiarid shrub communities. Wildlife Society Bulletin 34, 1458–1462.
| Limitations of thermal infrared imaging for locating neonatal deer in semiarid shrub communities.Crossref | GoogleScholarGoogle Scholar |
Caughley, G., and Grigg, G. C. (1981). Surveys of the distribution and density of kangaroos in the pastoral zone of South Australia, and their bearing on the feasibility of aerial survey in large and remote areas. Australian Wildlife Research 8, 1–11.
| Surveys of the distribution and density of kangaroos in the pastoral zone of South Australia, and their bearing on the feasibility of aerial survey in large and remote areas.Crossref | GoogleScholarGoogle Scholar |
Caughley, G., Sinclair, R. G., and Wilson, G. R. (1977). Numbers, distribution and harvesting rate of kangaroos on the inland plains of New South Wales. Australian Wildlife Research 4, 99–108.
| Numbers, distribution and harvesting rate of kangaroos on the inland plains of New South Wales.Crossref | GoogleScholarGoogle Scholar |
Chabot, D. (2009). Systematic evaluation of a stock unmanned aerial vehicle (UAV) system for small scale wildlife survey applications. M.Sc. Thesis, McGill University, Montreal.
Chabot, D., and Bird, D. M. (2012). Evaluation of an off‐the‐shelf unmanned aircraft system for surveying flocks of geese. Waterbirds 35, 170–174.
| Evaluation of an off‐the‐shelf unmanned aircraft system for surveying flocks of geese.Crossref | GoogleScholarGoogle Scholar |
Chabot, D., and Bird, D. M. (2015). Wildlife research and management methods in the 21st Century: where do unmanned aircraft fit in? Journal of Unmanned Vehicle Systems 3, 137–155.
| Wildlife research and management methods in the 21st Century: where do unmanned aircraft fit in?Crossref | GoogleScholarGoogle Scholar |
Choquenot, D. (1995). Assessing visibility bias associated with helicopter counts of feral pigs in Australia’s semi-arid rangelands. Wildlife Research 22, 569–577.
| Assessing visibility bias associated with helicopter counts of feral pigs in Australia’s semi-arid rangelands.Crossref | GoogleScholarGoogle Scholar |
Chrétien, L. P., Théau, J., and Ménard, P. (2015). Wildlife multispecies remote sensing using visible and thermal infrared imagery acquired from an unmanned aerial vehicle (UAV). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1, 241–248.
| Wildlife multispecies remote sensing using visible and thermal infrared imagery acquired from an unmanned aerial vehicle (UAV).Crossref | GoogleScholarGoogle Scholar |
Chrétien, L. P., Théau, J., and Ménard, P. (2016). Visible and thermal infrared remote sensing for the detection of white-tailed deer using an unmanned aerial system. Wildlife Society Bulletin 40, 181–191.
| Visible and thermal infrared remote sensing for the detection of white-tailed deer using an unmanned aerial system.Crossref | GoogleScholarGoogle Scholar |
Ditchkoff, S. S., Raglin, J. B., Smith, J. M., and Collier, B. A. (2005). Capture of white-tailed deer fawns using thermal imaging technology. Wildlife Society Bulletin 33, 1164–1168.
| Capture of white-tailed deer fawns using thermal imaging technology.Crossref | GoogleScholarGoogle Scholar |
Ditmer, M. A., Vincent, J. B., Werden, L. K., Iaizzo, P. A., Garshelis, D. L., and Fieberg, J. R. (2015). Bears show a physiological but limited behavioral response to unmanned aerial vehicles. Current Biology 25, 2278–2283.
| Bears show a physiological but limited behavioral response to unmanned aerial vehicles.Crossref | GoogleScholarGoogle Scholar | 26279232PubMed |
Dowle, M. (2018). data.table: extension of ‘data.frame’. R package version 1.11.4. Available at https://CRAN.R-project.org/package=data.table [verified 1 March 2018].
Edwards, G. P., Saalfeld, K., and Clifford, B. (2004). Population trend of feral camels in the Northern Territory. Australian Wildlife Research 31, 509–517.
| Population trend of feral camels in the Northern Territory.Crossref | GoogleScholarGoogle Scholar |
Evans, L. J., Jones, T. H., Pang, K., Saimin, S., and Goossens, B. (2016). Spatial ecology of estuarine crocodile (Crocodylus porosus) nesting in a fragmented landscape. Sensors 16, 1527.
| Spatial ecology of estuarine crocodile (Crocodylus porosus) nesting in a fragmented landscape.Crossref | GoogleScholarGoogle Scholar |
Fewster, R. M., and Pople, A. R. (2008). A comparison of mark–recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos. Wildlife Research 35, 320–330.
| A comparison of mark–recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos.Crossref | GoogleScholarGoogle Scholar |
Flodell, A., and Christensson, C. (2016). Wildlife surveillance using a uav and thermal imagery., M.Sc. Thesis, Linköping University, Linköping, Sweden.
Garner, D. L., Underwood, H. B., and Porter, W. F. (1995). Use of modern infrared thermography for wildlife population surveys. Environmental Management 19, 233–238.
| Use of modern infrared thermography for wildlife population surveys.Crossref | GoogleScholarGoogle Scholar |
Gentle, M., Finch, N., Speed, J., and Pople, A. (2018). A comparison of unmanned aerial vehicles (drones) and manned helicopters for monitoring macropod populations. Wildlife Research 45, 586–594.
| A comparison of unmanned aerial vehicles (drones) and manned helicopters for monitoring macropod populations.Crossref | GoogleScholarGoogle Scholar |
Gonzalez, L. F., Montes, G. A., Puig, E., Johnson, S., Mengersen, K., and Gaston, K. J. (2016). Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation’ Sensors 16, 97.
| Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation’Crossref | GoogleScholarGoogle Scholar |
Gooday, O. J., Key, N., Goldstien, S., and Zawar-Reza, P. (2018). An assessment of thermal-image acquisition with an unmanned aerial vehicle (UAV) for direct counts of coastal marine mammals ashore. Journal of Unmanned Vehicle Systems 6, 100–108.
| An assessment of thermal-image acquisition with an unmanned aerial vehicle (UAV) for direct counts of coastal marine mammals ashore.Crossref | GoogleScholarGoogle Scholar |
Graves, H. B., Bellis, E. D., and Knuth, W. M. (1972). Censusing white-tailed deer by airborne thermal infrared imagery. The Journal of Wildlife Management 36, 875–888.
| Censusing white-tailed deer by airborne thermal infrared imagery.Crossref | GoogleScholarGoogle Scholar |
Grierson, I. T., and Gammon, J. A. (2002). The use of aerial digital imagery for kangaroo monitoring. Geocarta International 17, 43–49.
Grigg, G. C., and Pople, A. R. (1999). Outcomes of the workshop: refining aerial surveys of kangaroos. Australian Zoologist 31, 317–320.
| Outcomes of the workshop: refining aerial surveys of kangaroos.Crossref | GoogleScholarGoogle Scholar |
Havens, K. J., and Sharp, E. J. (1998). Using thermal imagery in the aerial survey of animals. Wildlife Society Bulletin 26, 17–23.
Hilborn, R., and Mangel, M. (1997). ‘The Ecological Detective, Confronting Models with Data.’ (Princeton University Press: Princeton, NJ.)
Hodgson, A., Kelly, N., and Peel, D. (2013). Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study. PLoS One 8, e79556.
| Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study.Crossref | GoogleScholarGoogle Scholar | 24278203PubMed |
Hodgson, J. C., Mott, R., Baylis, S. M., Pham, T. T., Wotherspoon, S., Kilpatrick, A. D., Segaran, R. R., Reid, I., Terauds, A., and Koh, L. P. (2018). Drones count wildlife more accurately and precisely than humans. Methods in Ecology and Evolution 9, 1160–1167.
| Drones count wildlife more accurately and precisely than humans.Crossref | GoogleScholarGoogle Scholar |
Israel, M. (2011). A UAV-based roe deer fawn detection system. International Archives of Photogrammetry and Remote Sensing 38, 51–55.
Jones, G. P. I. V., Pearlstine, L. G., and Percival, H. F. (2006). An assessment of small unmanned aerial vehicles for wildlife research. Wildlife Society Bulletin 34, 750–758.
| An assessment of small unmanned aerial vehicles for wildlife research.Crossref | GoogleScholarGoogle Scholar |
Kingsford, R. T., Bino, G., and Porter, J. L. (2017). Continental impacts of water development on waterbirds, contrasting two Australian river basins: global implications for sustainable water use. Global Change Biology 23, 4958–4969.
| Continental impacts of water development on waterbirds, contrasting two Australian river basins: global implications for sustainable water use.Crossref | GoogleScholarGoogle Scholar | 28578561PubMed |
Kissell, R. E., and Nimmo, S. K. (2011). A technique to estimate white-tailed deer Odocoileus virginianus density using vertical-looking infrared imagery. Wildlife Biology 17, 85–92.
| A technique to estimate white-tailed deer Odocoileus virginianus density using vertical-looking infrared imagery.Crossref | GoogleScholarGoogle Scholar |
Lethbridge, M. R. (2017). ‘Thermal V 1.0.’. Software for interrogating thermal survey footage. (Flinders University: Adelaide, SA.)
Lethbridge, M. R., and Alexander, P. (2008). Comparing population growth rates using weighted bootstrapping: guiding the conservation management of Petrogale xanthopus xanthopus (yellow-footed rock-wallaby) Biological Conservation 141, 1185–1195.
| Comparing population growth rates using weighted bootstrapping: guiding the conservation management of Petrogale xanthopus xanthopus (yellow-footed rock-wallaby)Crossref | GoogleScholarGoogle Scholar |
Lethbridge, M. R., Saalfeld, K. A., and Edwards, G. P. (2016). Measured reductions in the density of camels under the Australian Feral Camel Management Project. The Rangeland Journal 38, 173–179.
| Measured reductions in the density of camels under the Australian Feral Camel Management Project.Crossref | GoogleScholarGoogle Scholar |
Lhoest, S., Linchant, J., Quevauvillers, S., Vermeulen, C., and Lejeune, P. (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 XL-3, 355–362.
| HOW MANY HIPPOS (HOMHIP): algorithm for automatic counts of animals with infra-red thermal imagery from UAV.Crossref | GoogleScholarGoogle Scholar |
Linklater, W. L., and Cameron, E. Z. (2002). Escape behaviour of feral horses during a helicopter count. Wildlife Research 29, 221–224.
| Escape behaviour of feral horses during a helicopter count.Crossref | GoogleScholarGoogle Scholar |
Marsh, H., and Saalfeld, W. K. (1990). The distribution and abundance of dugongs in the Great Barrier Reef Marine Park south of Cape Bedford. Australian Wildlife Research 17, 511–524.
| The distribution and abundance of dugongs in the Great Barrier Reef Marine Park south of Cape Bedford.Crossref | GoogleScholarGoogle Scholar |
Marsh, H. M., and Sinclair, D. F. (1989). Correcting for visibility bias in strip transect aerial surveys of aquatic fauna. The Journal of Wildlife Management 53, 1017–1024.
| Correcting for visibility bias in strip transect aerial surveys of aquatic fauna.Crossref | GoogleScholarGoogle Scholar |
Milborrow, S. (2018). earth: Multivariate Adaptive regression Splines, R package version 4.6.3, Available at https://CRAN.R-project.org/package=earth [verified 18 April 2018].
Moloney, P. D., Ramsey, D. S. L., and Scroggie, M. P. (2017). A state-wide aerial survey of kangaroos in Victoria. Arthur Rylah Institute for Environmental Research Technical Report Series No. 286. Department of Environment, Land, Water and Planning, Melbourne.
Pau, G., Fuchs, F., Sklyar, O., Boutros, M., and Huber, W. (2010). EBImage—an R package for image processing with applications to cellular phenotypes. Bioinformatics 26, 979–981.
| EBImage—an R package for image processing with applications to cellular phenotypes.Crossref | GoogleScholarGoogle Scholar | 20338898PubMed |
Pollock, K. H., and Kendall, W. L. (1987). Visibility bias in aerial surveys: a review of estimation procedures. The Journal of Wildlife Management 51, 502–510.
| Visibility bias in aerial surveys: a review of estimation procedures.Crossref | GoogleScholarGoogle Scholar |
Pople, A. R., Grigg, G. C., Cairns, S. C., Alexander, P., Beard, L. A., and Henzell, R. P. (1996). Trends in numbers and changes in the distribution of feral goats (Capra hircus) in the South Australia pastoral zone. Wildlife Research 23, 687–695.
| Trends in numbers and changes in the distribution of feral goats (Capra hircus) in the South Australia pastoral zone.Crossref | GoogleScholarGoogle Scholar |
Pople, A. R., Cairns, S. C., Clancy, T. F., Grigg, G. C., Beard, L. A., and Southwell, C. J. (1998). An assessment of the accuracy of kangaroo surveys using fixed-wing aircraft. Wildlife Research 25, 315–326.
| An assessment of the accuracy of kangaroo surveys using fixed-wing aircraft.Crossref | GoogleScholarGoogle Scholar |
Ratcliffe, N., Guihen, D., Robst, J., Crofts, S., Stanworth, A., and Enderlein, P. (2015). A protocol for the aerial survey of penguin colonies using UAVs. Journal of Unmanned Vehicle Systems 3, 95–101.
| A protocol for the aerial survey of penguin colonies using UAVs.Crossref | GoogleScholarGoogle Scholar |
R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at http://www.R-project.org/ [verified 1 March 2018].
Ribeiro-Gomes, K., Hernandez-Lopez, D., Ortega, J. F., Ballesteros, R., Poblete, T., and Moreno, M. A. (2017). Uncooled thermal camera calibration and optimisation of the photogrammetry process for UAV applications in agriculture. Sensors 17, 2173–2196.
| Uncooled thermal camera calibration and optimisation of the photogrammetry process for UAV applications in agriculture.Crossref | GoogleScholarGoogle Scholar |
Rowat, D., Gore, M., Meekan, M. G., Lawler, I. R., and Bradshaw, C. J. A. (2009). Aerial survey as a tool to estimate whale shark abundance trends. Journal of Experimental Marine Biology and Ecology 368, 1–8.
| Aerial survey as a tool to estimate whale shark abundance trends.Crossref | GoogleScholarGoogle Scholar |
Samuel, M. D., Garton, E., Schlegel, M. W., and Carson, R. G. (1987). Visibility bias during aerial surveys of elk in northcentral Idaho. The Journal of Wildlife Management 51, 622–630.
| Visibility bias during aerial surveys of elk in northcentral Idaho.Crossref | GoogleScholarGoogle Scholar |
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. The Ibis 154, 177–183.
| Fine‐scale bird monitoring from light unmanned aircraft systems.Crossref | GoogleScholarGoogle Scholar |
Scroggie, M. P., Moloney, P. D., and Ramsey, D. S. L. (2017). Design of an aerial survey to estimate the abundance of kangaroos in Victoria. Arthur Rylah Institute for Environmental Research Technical Report No. 280. Department of Environment, Land, Water and Planning, Melbourne.
Seber, G. A. F. (1982). ‘The Estimation of Animal Abundance and Related Parameters,’ 2nd edn, (Edward Arnold: London.)
Seymour, A. C., Dale, J., Hammill, M., Halpin, P. N., and Johnston, D. W. (2017). Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery. Scientific Reports 7, 45127.
| Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery.Crossref | GoogleScholarGoogle Scholar | 28338047PubMed |
Short, J., and Bayliss, P. (1985). Bias in aerial survey estimates of kangaroo density. Journal of Applied Ecology 22, 415–422.
| Bias in aerial survey estimates of kangaroo density.Crossref | GoogleScholarGoogle Scholar |
Southwell, C. (1996). Bias in aerial survey of feral goats in the rangelands of Western Australia. The Rangeland Journal 18, 99–103.
| Bias in aerial survey of feral goats in the rangelands of Western Australia.Crossref | GoogleScholarGoogle Scholar |
Southwell, C., Weaver, K., Sheppard, N., and Morris, P. (1993). Distribution and relative abundance of feral goats in the rangelands of eastern Australia. The Rangeland Journal 15, 331–333.
| Distribution and relative abundance of feral goats in the rangelands of eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Thomas, L., Buckland, S. T., Rexstad, E. A., Laake, J. L., Strindberg, S., Hedley, S. L., Bishop, J. R. B., Marques, T. A., and Burnham, K. P. (2010). Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology 47, 5–14.
| Distance software: design and analysis of distance sampling surveys for estimating population size.Crossref | GoogleScholarGoogle Scholar | 20383262PubMed |
Tschumperlé, D. (2004). CImg. Available at http://cimg.eu/reference/index.html [verified 1 March 2018].
Vermeulen, C., Lejeune, P., Lisein, J., Sawadogo, P., and Bouché, P. (2013). Unmanned aerial survey of elephants. PLoS One 8, e54700.
| Unmanned aerial survey of elephants.Crossref | GoogleScholarGoogle Scholar | 23658762PubMed |
Walter, M. J., and Hone, J. (2003). A comparison of 3 aerial survey techniques to estimate wild horse abundance in the Australian Alps. Wildlife Society Bulletin 31, 1138–1149.
Wich, S., Dellatore, D., Houghton, M., Ardi, R., and Koh, L. P. (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.
| A preliminary assessment of using conservation drones for Sumatran orang‐utan (Pongo abelii) distribution and density.Crossref | GoogleScholarGoogle Scholar |
