Protection of Coastal Shelter Forests Using UAVs: Individual Tree and Tree-Height Detection in Casuarina equisetifolia L. Forests

Casuarina equisetifolia L. plays a significant role in sandy, coastal regions for sand stabilization and windbreaks. However, C. forests are susceptible to plant diseases insect pests, resulting mortality due pure stands harsh natural environment. Mapping the distribution of detecting its height can inform forest-management decisions. Unmanned aerial vehicle (UAV) imagery, coupled with classical detection method, provide accurate information on tree-level forest parameters. Considering that accuracy forest-parameter estimation is impacted by various flight altitudes extraction parameters, purpose this study determine appropriate altitude parameters mapping using UAV imagery local maxima algorithm order monitor more accurately. A total 11 different 36 combinations circular smoothing window size (CSWS) fixed (FCWS) were tested, 796 trees corresponding positions image ground–tree heights used as reference. The results show combination 0.1 m CSWS 0.8 FCWS individual tree (ITD) tree-height achieved excellent (with an F1 score 91.44% ITD (EA) 79.49% detection). lower did not indicate higher detection. obtained within 60 m–80 meet requirements identification (F1 > 85% ITD; EA 75% estimation). This provides foundation monitoring applying algorithm, which may help forestry practitioners detect accurately, providing growth status.