2024 Volume 80 Issue 17 Article ID: 24-17235
Understanding the spatial distribution (canopy height and biomass) of seagrass meadows is important for improving and utilizing the various environmental values of seagrass meadows. However, conventional survey methods for the spatial distribution of seagrass face the challenge of achieving both efficiency and accuracy. In this study, point cloud data analysis methods using a UAV equipped with a green laser scanner were applied to two seagrass meadows with different vegetation and environments (eelgrass beds in Hokkaido and subtropical seagrass beds in Okinawa Prefecture) to estimate the spatial distribution of seagrass meadows. In the subtropical seagrass meadow, the measured vegetation height was 16 ± 4 cm (mean ± SD), while the analyzed height was 17 ± 2 cm. The Cloth Simulation Filter was suitable for the analysis of the eelgrass beds (R2 = 0.74, RMSE = 0.11 m). The spatial volume of vegetation estimated from the point cloud data was positively correlated with the wet weight of the vegetation. The slope of the regression equation differed between the two seagrass beds depending on differences in canopy height, shoot density and other factors.
