The goal of this research is to enhance supply chain efficiency and improve international competitiveness in the forest industry. Research includes ground-based LiDAR stem analysis for value optimization, discovering new methods to increase the efficiency of steep slope harvesting operations, moisture management models for biomass recovery, decision support models for biomass utilization on steep slopes and harvest scheduling methodologies for addressing uncertainty in forest planning.
This program area focuses on logging safety on steep slopes.
The Mechanized Harvesting Laboratory combines state-of-the-art computer-based forest harvesting machine simulation, mechanical analysis, operations research, and field-based research to increase the knowledge of modern mechanized harvesting systems. Our vision is to provide transformative research that supports technology-based experiential learning for modern forest harvesting systems.
This research is interested in active sustainable management of forest, by using various remote sensing techniques to acquire relevant information for the decision making process. Once raw data is collected, we develop, improve or test existing algorithms to supply the needed data for developing management plans or forecast forest dynamics. Our focus is in modeling forest understood in a broad sense using modern techniques, such as computer vision, fractals, or abstract algebra. The main instruments used for data acquisition are unmanned aerial systems equipped with lidar, RGB, and multispectral sensors.
The study aims to inform policy for Oregon and stakeholders by evaluating whether large-scale biochar production is technically feasible, logistically scalable, economically competitive and environmentally beneficial at the landscape scale. If the outcome suggests biochar production meets these minimum criteria, the study could potentially trigger industrial interest in supporting the development of forest-to-farm biochar markets, benefiting rural economies that are typically based on forest and agricultural commodities.
The Mechanized Harvesting Laboratory combines state-of-the-art computer-based forest harvesting machine simulation, mechanical analysis, operations research, and field-based research to increase the knowledge of modern mechanized harvesting systems. Our vision is to provide transformative research that supports technology-based experiential learning for modern forest harvesting systems.
This program area focuses on logging safety on steep slopes.
The study aims to inform policy for Oregon and stakeholders by evaluating whether large-scale biochar production is technically feasible, logistically scalable, economically competitive and environmentally beneficial at the landscape scale. If the outcome suggests biochar production meets these minimum criteria, the study could potentially trigger industrial interest in supporting the development of forest-to-farm biochar markets, benefiting rural economies that are typically based on forest and agricultural commodities.
This research is interested in active sustainable management of forest, by using various remote sensing techniques to acquire relevant information for the decision making process. Once raw data is collected, we develop, improve or test existing algorithms to supply the needed data for developing management plans or forecast forest dynamics. Our focus is in modeling forest understood in a broad sense using modern techniques, such as computer vision, fractals, or abstract algebra.