Kuva: Adam Sagar
In his doctoral dissertation, MSc (Tech) Anwar Sagar investigated how LiDAR sensing, simulation, and data-driven methods can improve tree stem quality assessment and quality monitoring in cut-to-length forest harvesting. He developed and evaluated an integrated framework combining machine-mounted LiDAR, simulation-based testing, and mobile laser scanning to support more objective and automated assessment before and after harvesting. The results demonstrate that LiDAR-based methods can reliably measure key stem and stand characteristics, detect stem defects, and assess harvesting quality, reducing reliance on subjective visual assessment and labour-intensive field measurements. The research provides a foundation for intelligent forest harvesting systems that can support operator decision-making and contribute to more consistent, efficient, and sustainable forest management.
The doctoral dissertation titled Integrating LiDAR Sensing, Simulation, and Decision Support for Automated Assessment of Tree Stem Quality in Cut-to-Length Forest Harvesting by MSc (Tech) Anwar Sagar will be publicly examined in the Faculty of Engineering and Natural Sciences at Tampere University on 16 October 2026. The dissertation is in the field of automation science and engineering.
The Opponent will be Professor Ola Lindroos from the Swedish University of Agricultural Sciences, Sweden. The Custos will be Professor Reza Ghabcheloo from the Faculty of Engineering and Natural Sciences.