A Novel UAV- and AI-Based Remote Sensing Approach for Quantitative Monitoring of Jellyfish Populations: A Case Study of Acromitus flagellatus in Qinglan Port
文献类型：期刊论文
| 作者 | Zhang, Fang1,2,3; Wang, Shuo2,3; Qiu, Yanhao4; Wang, Nan1,2,3; Sun, Song1,2,3; Bi, Hongsheng5 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2025-08-31 |
| 卷号 | 17期号:17页码:20 |
| 关键词 | UAV low-altitude remote sensing
jellyfish population monitoring
bell diameter measurement model
|
| DOI | 10.3390/rs17173020 |
| 通讯作者 | Zhang, Fang(zhangfang@qdio.ac.cn) |
| 英文摘要 | The frequency of jellyfish blooms in marine ecosystems has been rising globally, attracting significant attention from the scientific community and the general public. Low-altitude remote sensing with Unmanned Aerial Vehicles (UAVs) offers a promising approach for rapid, large-scale, and automated image acquisition, making it an effective tool for jellyfish population monitoring. This study employed UAVs for extensive sea surface surveys, achieving quantitative monitoring of the spatial distribution of jellyfish and optimizing flight altitude through gradient experiments. We developed a "bell diameter measurement model" for estimating jellyfish bell diameters from aerial images and used the Mask R-CNN algorithm to identify and count jellyfish automatically. This method was tested in Qinglan Port, where we monitored Acromitus flagellatus populations from mid-April to mid-May 2021 and late May 2023. Our results show that the UAVs can monitor jellyfish with bell diameters of 5 cm or more, and the optimal flight height is 100-150 m. The bell diameter measurement model, defined as L = 0.0103 x H x N + 0.1409, showed no significant deviation from field measurements. Compared to visual identification by human experts, the automated method achieved high accuracy while reducing labor and time costs. Case analysis revealed that the abundance of A. flagellatus in Qinglan Port initially increased and then decreased from mid-April to mid-May 2021, displaying a distinct patchy distribution. During this period, the average bell diameter gradually increased from 15.0 +/- 3.4 cm to 15.5 +/- 4.3 cm, with observed sizes ranging from 8.2 to 24.5 cm. This study introduces a novel, efficient, and cost-effective UAV-based method for quantitative monitoring of large jellyfish populations in surface waters, with broad applicability. |
| WOS关键词 | SPATIAL-RESOLUTION ; SUN GLINT ; ABUNDANCE ; DYNAMICS ; SEA ; CONSEQUENCES ; ECOLOGY ; BLOOMS ; IMAGES |
| 资助项目 | National Key Research and Development Program of China ; [2023YFC3108202] ; [LSKJ202203704] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001570146200001 |
| 出版者 | MDPI |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/203341]  |
| 专题 | 海洋研究所_海洋生态与环境科学重点实验室 |
| 通讯作者 | Zhang, Fang |
| 作者单位 | 1.Qingdao Marine Sci & Technol Ctr, Lab Marine Ecol & Environm Sci, Qingdao 266237, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Marine Ecol & Environm Sci, Qingdao 266071, Peoples R China 3.Univ Chinese Acad Sci, Coll Marine Sci, Qingdao 266400, Peoples R China 4.Jiangsu Huanghai Ecol Environm Technol Co Ltd, Yancheng 224000, Peoples R China 5.Univ Maryland, Ctr Environm Sci, Solomons, MD 20688 USA |
| 推荐引用方式 GB/T 7714 | Zhang, Fang,Wang, Shuo,Qiu, Yanhao,et al. A Novel UAV- and AI-Based Remote Sensing Approach for Quantitative Monitoring of Jellyfish Populations: A Case Study of Acromitus flagellatus in Qinglan Port[J]. REMOTE SENSING,2025,17(17):20. |
| APA | Zhang, Fang,Wang, Shuo,Qiu, Yanhao,Wang, Nan,Sun, Song,&Bi, Hongsheng.(2025).A Novel UAV- and AI-Based Remote Sensing Approach for Quantitative Monitoring of Jellyfish Populations: A Case Study of Acromitus flagellatus in Qinglan Port.REMOTE SENSING,17(17),20. |
| MLA | Zhang, Fang,et al."A Novel UAV- and AI-Based Remote Sensing Approach for Quantitative Monitoring of Jellyfish Populations: A Case Study of Acromitus flagellatus in Qinglan Port".REMOTE SENSING 17.17(2025):20. |
入库方式： OAI收割
来源：海洋研究所
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