This project aims to develop automated methods for monitoring vegetation structural and functional metrics at fine levels of spatial detail (tree and branch level) across local to regional scales (100s ha) by addressing a missing drone-based LiDAR processing capability. Algorithms will be developed and verified to produce accurate and precise tree and woody vegetation models down to cm accuracy from 3D point cloud data across both native and agricultural landscapes. This aligns with the Maya Nula SmartSat research program. These 3D models will allow vegetation structural and functional baseline metrics to be automatically extracted at both individual tree and entire site levels, namely: stem density, stem diameter, crown height, crown width, woody volume, and aboveground biomass.