The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Precision wildlife monitoring using unmanned aerial vehicles
Open accessAbstract
Unmanned aerial vehicles (UAVs) represent a new frontier in environmental research. Their use has the potential to revolutionise the field if they prove capable of improving data quality or the ease with which data are collected beyond traditional methods. We apply UAV technology to wildlife monitoring in tropical and polar environments and demonstrate that UAV-derived counts of colony nesting birds are an order of magnitude more precise than traditional ground counts. The increased count precision afforded by UAVs, along with their ability to survey hard-to-reach populations and places, will likely drive many wildlife monitoring projects that rely on population counts to transition from traditional methods to UAV technology. Careful consideration will be required to ensure the coherence of historic data sets with new UAV-derived data and we propose a method for determining the number of duplicated (concurrent UAV and ground counts) sampling points needed to achieve data compatibility.
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Cited by
Perspectives in machine learning for wildlife conservation
Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., Mathis, A., Mathis, M. W., van Langevelde, F., Burghardt, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-27980-y · Cited by 740
Unmanned aircraft systems as a new source of disturbance for wildlife: A systematic review
Mulero-Pázmány, M., Jenni-Eiermann, S., Strebel, N., Sattler, T., Negro, J. J., & Tablado, Z. (2017) · PLOS ONE · doi:10.1371/journal.pone.0178448 · Cited by 319
ATRW: A Benchmark for Amur Tiger Re-identification in the Wild
Li, S., Li, J., Tang, H., Qian, R., & Lin, W. (2020) · Proceedings of the 28th ACM International Conference on Multimedia · doi:10.1145/3394171.3413569 · Cited by 121
Schroeder, N. M., Panebianco, A., Gonzalez Musso, R., & Carmanchahi, P. (2020) · Royal Society Open Science · doi:10.1098/rsos.191482 · Cited by 66
Metadata
- Authors
- Hodgson, J. C., Baylis, S. M., Mott, R., Herrod, A., & Clarke, R. H.
- Venue
- Scientific Reports
- Published
- 2016-03-17
- Volume
- 6
- Issue
- 1
- Pages
- 22574-22574
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2331725058
- Cited by
- 474
- References
- 14
- FWCI
- 37.48
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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