SIMULATING VARIOUS TERRESTRIAL AND UAV LIDAR SCANNING CONFIGURATIONS FOR UNDERSTORY FOREST STRUCTURE MODELLING
- 1GIScience Research Group, Institute of Geography, Heidelberg University, Germany
- 2Laboratory for Geometric Modeling and Multimedia Algorithms, Faculty of Electrical Engineering and Computer Science, University of Maribor, Slovenia
- 3Department of Geomatics, National Cheng Kung University, Tainan, Taiwan
- 4Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, the Netherlands
- 5Heidelberg Center for the Environment (HCE), Heidelberg University, Germany
Keywords: Forest structure, understory, laser scanning simulation, full waveform, 3D point cloud analysis, field campaign planning
Abstract. Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.