https://scholars.lib.ntu.edu.tw/handle/123456789/641341
標題: | Application of drones and artificial intelligence in flocking birds | 作者: | Chiang, Kung Kuo HSIAO-WEI YUAN |
關鍵字: | artificial intelligence model | breeding colony. | disturbance | flight initiation distances | Unmanned aerial vehicles (UAVs) | 公開日期: | 1-一月-2023 | 來源出版物: | Asia-Pacific Microwave Conference Proceedings, APMC | 摘要: | The emergence of unmanned aerial vehicles (UAVs) has expanded the boundaries of traditional bird survey methods, enabling researchers to reach many previously inaccessible targets. However, UAVs can potentially disrupt bird species and remain a concern for researchers. This study indicates that among 11 species of wintering waterbirds, there is a significant negative correlation between bird size and the alert distance from UAVs. In the case of breeding Bridled Terns (Thalasseus bernsteini), their alert distance to UAVs during chick stage is significantly greater than during egg incubation stage. Additionally, experiments on Eurasian Teals (Anas crecca) and Black-winged Stilts (Himantopus himantopus) have shown a trend of shortening their alert distances to UAVs with repeated testing over a short period.Population estimation of a large breeding colony is an important indicator for planning conservation efforts. However, traditional methods of estimating their population is both time-consuming and labor-intensive, limiting the research team's energy for other studies. To address this situation, this study has developed an artificial intelligence model capable of automatically counting the population of terns. By replacing traditional counting methods with this model, work efficiency can be improved, allowing the research team to contribute to a broader range of research endeavors. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/641341 | ISBN: | 9781665494182 | DOI: | 10.1109/APMC57107.2023.10439851 |
顯示於: | 森林環境暨資源學系 |
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