海洋渔业2026，Vol.48Issue(3)：329-340,12.
基于YOLOv8和高分遥感的长江口日本鳗鲡苗捕捞网具分布变化监测研究
Monitoring of distribution changes of fishing gears for Anguilla japonica fry in the Yangtze Estuary based on YOLOv8 and high-resolution remote sensing
摘要
Abstract
Anguilla japonica fishing is a key driver shaping the sustainability of wild eel resources,so up-to-date information on fishing effort has become an urgent concern for fisheries managers.Conventional remote-sensing techniques,however,fail to provide effective monitoring,because the gear is extremely small and sea conditions are highly complex.To test whether very-high-resolution satellite imagery can be used to track Anguilla japonica fishing dynamics,we applied a YOLOv8 object-detection model to map and monitor the distribution of fishing nets over two consecutive years(2023 and 2024)in a section of the East China Sea east of Chongming Island at the mouth of the Yangtze River.Training on a single-year sample set proved insufficient for reliable gear detection,whereas a hybrid dataset that combined imagery from both years markedly improved recognition accuracy and the model's generalization under complex sea states,yielding precision(P)and mean average precision(mAP@0.50)values above 0.90.The monitoring results reveal a pronounced year-on-year increase in the number of nets deployed in 2024,indicating large inter-annual variability in fishing intensity and underscoring the need for more effective,dynamic fishing-effort monitoring.The hybrid-dataset,deep-learning strategy developed provides a robust technical reference for implementing dynamic monitoring and management of China's Anguilla japonica fishing.关键词
日本鳗鲡苗/高分辨率遥感/目标识别/YOLO/动态监测/渔业管理Key words
Anguilla japonica fry/high-resolution remote sensing/object recognition/YOLO/dynamic monitoring/fisheries management分类
信息技术与安全科学引用本文复制引用
朱鹏飞,周为峰,王斐..基于YOLOv8和高分遥感的长江口日本鳗鲡苗捕捞网具分布变化监测研究[J].海洋渔业,2026,48(3):329-340,12.基金项目
国家重点研发计划项目(2024YFD2401000) （2024YFD2401000）
上海市"科技创新行动计划"(24N12800500) （24N12800500）
