The Identification of Exposed Beachrocks on South China Sea Islands Based on UAV Images

Beachrocks are common coastal sedimentary rocks in tropical and subtropical seas. They are widely spread especially in islands and coastal areas. These rocks are important for island geological evolution research. Research on beachrocks aids in protecting island ecosystems and enhances islands’ ability to prevent and mitigate damage from natural disasters. This study uses unmanned aerial vehicle (UAV) images and the U-Net model based on deep learning to identify beachrocks. To enhance identification accuracy, the efficient channel attention (ECA) mechanism was integrated, leading to improvements of 0.49% in overall accuracy, 1.41% in precision, 0.97% in recall, 1.10% in F1-score, and 2.09% in intersection over union (IoU) compared to the baseline U-Net model. The final results demonstrate that the model effectively identified beachrocks, achieving 97.47% accuracy, 93.27% precision, 94.73% recall, 93.95% F1-score, and 88.65% IoU. This study offers a valuable tool for island geological evolution research and supports the development of large-scale island conservation efforts.