| Autor: |
Olivia Lappin, Jared A. Elmore, Landon R. Jones, Emma A. Schultz, Raymond B. Iglay, Mark D. McConnell |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Ecological Solutions and Evidence, Vol 5, Iss 1, Pp n/a-n/a (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2688-8319 |
| DOI: |
10.1002/2688-8319.12306 |
| Popis: |
Abstract The presence and abundance of Northern Bobwhite Colinus virginianus often relies on imprecise methods (e.g. fall covey counts), which can lead to inaccurate estimates resulting in poor management practices. Drones equipped with thermal sensors have proven beneficial for monitoring wildlife but still require sufficient field validation regarding precision. We tested the application of thermal drones for locating and counting Northern Bobwhite in Mississippi, USA. We conducted flights over known locations of Northern Bobwhite representing three individual, radio‐marked birds during the breeding season and seven covey locations during the wintering season shortly after dusk. Individuals and coveys were located in 67% and 86% of flights, respectively. In some scenarios, bobwhite could be seen from altitudes of 120 m because heat signatures of multiple individuals grouped together in the covey provided an easily recognisable feature, in contrast to individual birds alone. Counts were accurate for two coveys and underestimated remaining coveys, because individual birds were sometimes visually obstructed from above. The small body size of bobwhite results in few pixels in thermal images and depends on ground sampling distance as a function of flight altitude. Our flights were tested at known vicinities of bobwhite locations, yet our method shows promise for locating unknown coveys as well. Future systematic methods may benefit from automated image recognition using computer vision and machine learning to improve count accuracy and save time, costs and labor. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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