@article{Liu2026, 
author = {Jianbo Liu and Chunhua Chen and Dandan Chen and Yong Pang and Yuebo Hu and Jinjia Guo},
title = {Research on Multispectral Aerial Survey-Based Retrieval of Seagrass Bed Coverage in Tropical Marine Coastals},
year = {2026},
journal = {Periodical of Ocean University of China},
volume = {56},
number = {8},
pages = {148-154},
keywords = {unmanned aerial vehicle, multispectral, seagrass bed, Houhai Village, seagrass coverage, clustering-based unsupervised classification},
url = {https://www.sciopen.com/article/10.16441/j.cnki.hdxb.20250286},
doi = {10.16441/j.cnki.hdxb.20250286},
abstract = {To explore the applicability of multispectral remote sensing technology for seagrass bed investigation in coastal waters, this study selected the seagrass beds along the coast of Houhai Village in Sanya as the research object. Aerial surveys were conducted using a multispectral unmanned aerial vehicle (UAV) to obtain high-resolution orthophotos and the normalized difference vegetation index (NDVI). By combining these data with an unsupervised clustering classification method, seagrass distribution identification and area quantification were achieved. The results showed that this method could effectively identify patchily distributed seagrass. The total seagrass bed area in the study region was 14633.1 m2, of which the area of concentrated seagrass distribution was 6279.8 m2, and the actual seagrass-covered area was 4501.5 m2. Based on these results, this study proposed a method for calculating seagrass bed coverage as the ratio of the seagrass distribution area to the defined monitoring zone area. The impact of monitoring zone definition on coverage calculation results was systematically analyzed, and the coverage of seagrass beds along the coast of Houhai Village in Sanya was determined to be 19.4%. Compared with traditional seagrass coverage estimation methods, multispectral UAV remote sensing technology significantly improved the monitoring coverage, efficiency, and objectivity of seagrass assessments, demonstrating strong applicability and reliability. This approach provides an effective technical means for achieving routine and standardized ecological monitoring of seagrass beds.}
}