On November 11, 2025, Sonja Maas will defend her master thesis on “Comparing LiDAR-Based Acquisition Strategies for Forest Management Planning in a Mature Beech Stand” at 12:30 in seminar room 3, John-Skilton-Str. 4a.
From the abstract: Forests are inherently important for life on earth as we know it. Challenges like climate change and biodiversity loss enhance the importance of sustainable forest management planning and monitoring. This thesis investigates the potential and limitations of four LiDAR-based remote sensing platforms for forest monitoring and management in a mature beech stand in Germany. Through a comparative analysis of acquisition trajectories and sensor types, the study demonstrates that stationary and mobile terrestrial LiDAR excels in measuring stem-level parameters and has the ability to aid forest management through stem quality assortment analysis and timber volume estimation. However, it faces challenges in scanning the upper canopy, particularly during periods of dense foliage. Conversely, airborne and UAV sensors are highly effective in estimating crown characteristics, yet struggle with individual tree and stem measurements due to occlusion and lower spatial detail. The findings highlight that no single LiDAR platform captures all essential forest metrics, and that strategic integration of different systems, combined with well planned survey trajectories, is required to achieve comprehensive, high-quality stand and tree-level information.
1st Supervisor: Dr. Julian Fäth
2nd Supervisor: Prof. Dr. Tobias Ullmann
