Phd Candidate Oregon State University, United States
This study aims to develop and validate a robust methodology for accurately predicting site index in the Pacific Northwest region within the context of repeated forest inventories, utilizing LiDAR data. The successful implementation of this methodology could significantly enhance the efficiency and cost-effectiveness of forest management practices in the region.
Learning Objectives:
1. Understand the need for technological advancements in forest inventory and how the need can be balanced with Airborne Laser Scanning (ALS) data, specifically focusing on site index estimation using repeated ALS-based forest inventories.
2. Understand the potential of ALS data for site productivity assessment and evaluate how incorporating ALS data in forest inventory can be used to improve existing site index estimates for various forestry applications.
