- Open Access
Possibility of applying unmanned aerial vehicle (UAV) and mapping software for the monitoring of waterbirds and their habitats
Journal of Ecology and Environment volume 41, Article number: 21 (2017)
Conventional bird observation methods are line survey or point count method by bare eyes or through binoculars or telescopes. But in this study, the possibility of monitoring waterbirds using drones beyond the conventional research methods was explored. It also describes the direction of producing and accumulating images of waterbird habitats as a method to efficiently determine changes in waterbird habitats.
From the study, it was concluded that waterbird monitoring using drones was a new monitoring technique which could be applied to the field and 26 kinds of waterbirds were observed. In the case of a drone with a single lens, it was difficult to identify objects because the size of the subject was too small at a certain altitude. In this case, zoom lens can be an alternative. It has also been verified that image analysis software can be used to accumulate images of waterbird habitats.
If various kinds of advanced drones and cameras are used, it would be possible to monitor larger areas including the areas that are difficult for human access and to observe more waterbirds and wider habitats.
This study explored the possibility to apply drones as a method to monitor waterbirds and their habitats in the Upo wetland in Korea. As wetland is ecologically located at the border between the terrestrial ecosystem and aquatic ecosystem, it is considered to be a habitat with high biodiversity and important ecological functions (Bernard and Tuttle 1998). The Upo wetland, the subject area of this study, was registered as a wetland in 1998 by the Ramsar Convention, and it has been managed as wetland preservation area by the Ministry of Environment of Korea since 1999. Additionally, as it has fewer damages out of development than any other wetland, it provides stable habitat and shelter to a variety of waterbirds including winter visitors. Birds in the Upo wetland were mainly surveyed by Kang and Hahm (1997) and Kim (2001). In particular, Kim (2001) surveyed and reported 133 species of birds. However, as those studies were performed through classical observation methods such as line survey or point count method by bare eyes or with binoculars and telescopes (Bibby et al. 2000), they are different from this study which uses drones. From the perspective of the results, they are fundamentally different from this study as they include general bird species as well as waterbirds.
Recently, applications of drones to wild animal monitoring have been rapidly increasing worldwide (Christie et al. 2016; Ivosevic et al. 2015; 2017; Jones et al. 2006; Koh and Wich 2012; Linchant et al. 2015). In particular, monitoring studies targeting birds that are physically difficult to access or susceptible to human interference have been constantly made using drones (Hodgson et al. 2016; Sarda-Palomera et al. 2012).
As described above, surveys on birds in the Upo wetland have been made many times for the time being but interest in environmental changes of habitats affecting bird communities was not very high. Accordingly, in this study, it was tried to discuss storing and accumulating data on environments of habitats or resting place of waterbirds as well as monitoring waterbirds using drones.
In this study, a few commonly used rotary drone models were selected to monitor waterbird community and habitat. In this study, appropriate shooting criteria were proposed according to targets by changing camera and flight method depending on the subject of observation (waterbird community or habitat) and the monitoring possibility of waterbird using drones was reviewed. Additionally, it was tried to describe how to make and store various images such as orthomosaic images using image analysis software in order to quickly and accurately determine changes in habitats.
Survey area and time
The survey area was the Upo wetland located in Changnyeong-gun, Kyungsangnam-do province in Korea. The area with abundant waterbird population was selected as a subject area (Fig. 1), and photos were taken 38 times in total from May 2015 to December 2016 including four seasons to identify diverse migratory birds and resident birds.
To observe the waterbird communities and their habitats in the Upo wetland and to identify suitable drones and cameras, photos were taken using drones such as Phantom 2 Vision+, Inspire 1, and Phantom 4 (DJI, China) and cameras such as Zenmuse ×3 and Zenmuse Z3 (DJI, China). Detailed specifications of drones and cameras used for the survey are shown in Table 1. Waterbird observation results were also recorded in video form at various altitudes through manual flight of the aforementioned drones, and habitat status observation results were collected in the form of photographs through automatic flight according to the flight path setting (Fig. 2).
Videos of the waterbirds taken in the field were identified and classified by a bird expert on the monitor. Based on the identification and classification results, list of waterbird species was created. The aerial photos of the waterbird habitat taken in the field were edited using photogrammetry software such as Pix4Dmapper Pro (Pix4D, Switzerland) and PhotoScan Professional (Agisoft, Russia). As the aforementioned two programs can be set to capture images by superimposing the images themselves using GPS coordinates, a single image can be produced and orthomosaic images can be produced through geometric correction by automatic air trigonometry (Siebert and Teizer 2014; Lee and Choi 2015). Habitat data are stored and managed in the form of images through these techniques.
Results and discussion
Identification of waterbird community through manual flight of drones and exploration of possibilities
As the result of surveys on waterbird communities in the Upo wetland using a camera mounted on drones, a total of 26 species of waterbirds including Cygnus Cygnus, a natural monument and grade II endangered wildlife were identified (Table 2). In case of Phantom 2 Vision+, Inspire 1, and Phantom 4 (DJI, China) equipped with 20-mm single-lens camera, it was difficult to identify species of waterbirds as waterbird subjects for photography were too small in the photos when they were taken at the altitude where waterbirds are not disturbed from the drones’ flight (at least 30 m in altitude). When the altitude of the drone is less than 25 m, most of waterbirds were found to be disturbed or interfered with by flying drones and they flew into the air or moved quickly over the surface. In particular, Anser fabalis, a typical winter bird, showed a tendency to react more sensitively than other species. There was a situation that they might collide with a drone when they soared up to the sky. However, Zenmuse Z3 (DJI, China) that can be mounted on the Inspire 1 has built-in ×3.5 optical zoom function and it was possible to enlarge the size of the subject for species identification. In addition, it was possible to enlarge the subject up to 7 times using digital zoom (×2) on the screen. Accordingly, it was found that Zenmuse Z3 camera could shoot at a level allowing accurate identification even when it took photos at the altitude that would not give any stress to waterbirds (Fig. 3).
Although in this study various kinds of drones and cameras were used for shooting, subjects that could not be identified because it was taken too small were excluded from the study. Furthermore, there were some times when photos were not taken due to weather conditions and occurrence of avian influenza (AI). It seems that species diversity is lower than previous studies because of aforementioned reasons. Additionally, as camera lens of Phantom 2 Vision+ is made to provide a wider angle of view, it made distortion of the edge of the screen unlike Phantom 4 or Inspire 1.
Acquisition and accumulation of images of habitats through automatic flight of drones
We have collected photos of subject site through automatic flight in order to accumulate image data of waterbird habitat, and photos were taken in every survey with waterbird community monitoring to easily identify seasonal changes. At the same time, we tried to identify the most appropriate shooting options by varying the conditions of shooting options. For example, on August 17, 2016, 163 photos were collected using Inspire 1 (Zenmuse ×3 camera) at the altitude of 40 m through double grid mission. Details of photo-taking options are shown in Fig. 4. From the collected 163 images, a high-resolution orthomosaic image was produced through image analysis software such as PhotoScan Professional (Agisoft, Russia) or Pix4D mapper Pro (Pix4D, Switzerland) (Fig. 5). Photographs stored and managed as such can be used more efficiently to identify waterbird habitat environmental factors. It is considered that they may be useful for long-term ecological monitoring to observe changes according to space and time.
Additionally, it was found that image files generated by image analysis software are superimposed on a relatively accurate location of Google Earth through the GPS coordinate system (Fig. 6), and that the resolution is higher than the surrounding images captured by the satellite. In addition, it is difficult to quickly respond to various environmental changes such as habitat destruction as satellite images are large in size and cannot be updated in real time because of relatively longer shooting interval. On the other hand, the results of aerial photographs using drones can be great help in monitoring small-scale areas as they can be collected and processed quickly when needed.
Conventional bird observation methods are line survey or point count method by bare eyes or through binoculars or telescopes. But in this study, the possibility of monitoring waterbirds using drones beyond the conventional research methods was described. Additionally, not only observation of waterbirds but also method to accumulate images of waterbird habitat was searched for. As a result of this study, it was confirmed that waterbird monitoring using drones can be applied to the field as a new monitoring technique, and in total, 26 species of waterbirds were observed. This study applied rotary wing drones only. But if fixed wing drones are used considering conditions of the survey site, a long-term monitoring can be made under the condition that it less interferes with waterbirds by reducing the noise and vibration. In the case of a drone with a single lens, it was difficult to identify the subject because the size of the subject was too small. In such a case, a zoom in-out lens may be an alternative.
Additionally, it was confirmed that images of waterbird habitat could be accumulated through commercially used image analysis software such as Pix4D mapper Pro (Pix4D, Switzerland) and PhotoScan professional (Agisoft, Russia). Such data can be used to help quick and easy identification of the status of waterbird habitat by seasonal or environmental changes due to specific causes.
Furthermore, if advanced drones and cameras are used, it is possible to survey larger areas and to monitor even the most inaccessible areas. Consequently, more species, individuals and habitat can be observed. Besides, it is necessary to explore the possibilities of the method to survey waterbird quantitatively using drones.
Global positioning system
Bernard, J. M., & Tuttle, R. W. (1998). Stream corridor restoration: priciple, processes, and practices. In D. Hayes (Ed.), Engineering approaches to ecosystm restoration (pp. 320–325). American Society of Civil Engineers.
Bibby, C. J., Burgess, N. D., Hill, D. A., & Mustoe, S. H. (2000). Bird census technique. London: Academic.
Christie, K. S., Gilbert, S. L., Brown, C. L., Hatfield, M., & Hanson, L. (2016). Unmanned aircraft systems in wildlife research: current and future applications of a transformative technology. Frontiers in Ecology and the Environment, 14, 241–251.
Hodgson, J. C., Baylis, S. M., Mott, R., Herrod, A. H., & Clarke, R. H. (2016). Precision wildlife monitoring using unmanned aerial vehicles. Scientific Reports, 6, 22574. doi:10.1038/srep22574.
Ivosevic, B., Han, Y.-G., Cho, Y., & Kwon, O. (2015). The use of conservation drones in ecology and wildlife research. Journal of Ecology and Environment, 38, 113–118.
Ivosevic, B., Han, Y.-G., & Kwon, O. (2017). Monitoring butterflies with an unmanned aerial vehicle: current possibilities and future potentials. Journal of Ecology and Environment, 41, 12. doi:10.1186/s41610-017-0028-1.
Jones, G. P., Pearlstine, L. G., & Percival, H. F. (2006). An assessment of small unmanned aerial vehicles for wildlife research. Wildlife Society Bulletin, 34, 750–758.
Kang, J. H., & Hahm, K. H. (1997). The birds of the Upo wetland. The Korean Journal of Ornithology, 4, 35–46.
Kim, S. K. (2001). An analysis of Avifauna and community structure of waterbirds at Woopo wetland, Prov. Kyung-nam. MS Thesis, Kyungpook National University, Daegu.
Koh, L. P., & Wich, S. A. (2012). Dawn of drone ecology: low-cost autonomous aerial vehicles for conservation. Tropical Conservation Science, 5, 121–132.
Lee, S. J., & Choi, Y. S. (2015). Topographic survey at small-scale open-pit mines using a popular rotary-wing unmanned aerial vehicle (drone). Tunnel & Underground Space, 25, 462–469.
Linchant, J., Lisein, J., Semeki, J., Lejeune, P., & Vermeulen, C. (2015). Are unmanned aircraft systems (UASs) the future of wildlife monitoring? A review of accomplishments and challenges. Mammal Review, 45, 239–252.
Sarda-Palomera, F., Bota, G., Vinolo, C., Pallares, O., Sazatornil, V., Brotons, L., Gomariz, S., & Sarda, F. (2012). Fine‐scale bird monitoring from light unmanned aircraft systems. Ibis, 154, 177–183.
Siebert, S., & Teizer, J. (2014). Mobile 3D mapping for surveying earthwork projects using an unmanned aerial vehicle (UAV) system. Automation in Construction, 41, 1–14.
This subject is supported by Korea Ministry of Environment (MOE) as “Public Technology Program based on Environmental Policy (2014000210003)”.
This subject is supported by the Korea Ministry of Environment (MOE) as “Public Technology Program based on Environmental Policy (2014000210003)”.
Availability of data and materials
In this study, Y-GH mainly collected images with UAV and analyzed the image data using various software, and was a major contributor in writing the manuscript. SHY mainly contributed to identifying the waterbirds on the images taken by drones and made the list of species. OK mainly designed this work and revised the paper totally. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Han, YG., Yoo, S.H. & Kwon, O. Possibility of applying unmanned aerial vehicle (UAV) and mapping software for the monitoring of waterbirds and their habitats. j ecology environ 41, 21 (2017). https://doi.org/10.1186/s41610-017-0040-5
- Water bird
- Mapping software