Exec. Dir. & Prof. Ecological Restoration Institute & School of Forestry, NAU Flagstaff, Arizona, United States
Advancements in lidar and deep learning provide faster, scalable, and potentially more accurate methods for assessing coarse woody debris (CWD) compared to traditional approaches like Brown’s transects. While deep learning tools show great promise in accurately analyzing forest structures for management purposes, some challenges with estimations remain.
Learning Objectives:
Upon completion, participants will be able to describe various types of lidar and understand its applicability in assessing course woody debris
Upon completion, participants will be able to effectively communicate how lidar are and deep learning are changing the way we assess forest conditions to a diverse audience
Upon completion, participants will be able articulate why assessing course we debris with Lidar and deep learning is it difficult task.
