Graduate Student Purdue University West Lafayette, Indiana, United States
Tree-level forest monitoring and measurements is crucial for precision forestry but particularly challenging for natural broadleaf forests. Using UAS-RGB imagery acquired during mid-fall season, a two-step tree crown delineation algorithm is developed for precision forestry in broadleaf forests. This allows for individual tree monitoring showcasing innovative techniques for understanding forests.
Learning Objectives:
Upon completion, participants will be able to describe the challenges in segmenting individual tree in natural hardwood forests.
Upon completion participants will be able to conduct the two-step segmentation procedure to delineate individual crowns for a natural broadleaf forest.
