Articles by Sruthi M. Krishna Moorthy

Terrestrial laser scanning (TLS) has been applied to estimate forest wood volume based on detailed 3D tree reconstructions from point cloud data. However, sources of uncertainties in the point cloud data (alignment and scattering errors, occlusion, foliage...) and the reconstruction algorithm type and parameterisation are known to affect the reconstruction, especially around finer branches. To better understand the impacts of these uncertainties on the accuracy of TLS-derived woody volume, high-quality TLS scans were collected in leaf-off conditions prior to destructive harvesting of two forest-grown common ash trees (Fraxinus excelsior L.; diameter at breast height ~28 cm, woody volume of 732 and 868 L). We manually measured branch diameters at 265 locations in these trees. Estimates of branch diameters and tree volume from Quantitative Structure Models (QSM) were compared with these manual measurements. The accuracy of QSM branch diameter estimates decreased with smaller branch diameters. Tree woody volume was overestimated (+336 L and +392 L) in both trees. Branches measuring < 5 cm in diameter accounted for 80% and 83% of this overestimation respectively. Filtering for scattering errors or improved coregistration approximately halved the overestimation. Range filtering and modified scanning layouts had mixed effects. The small branch overestimations originated primarily in limitations in scanner characteristics and coregistration errors rather than suboptimal QSM parameterisation. For TLS-derived estimates of tree volume, a higher quality point cloud allows smaller branches to be accurately reconstructed. Additional experiments need to elucidate if these results can be generalised beyond the setup of this study.

• Demol, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium; PLECO – Plants and Ecosystems, Faculty of Science, Antwerp University, Universiteitsplein 1, B-2610 Wilrijk, Belgium https://orcid.org/0000-0002-5492-2874 E-mail: miro.demol@ugent.be
• Wilkes, UCL Department of Geography, Gower Street, London WC1E 6BT, UK; NERC National Centre for Earth Observation (NCEO), UK https://orcid.org/0000-0001-6048-536X E-mail: p.wilkes@ucl.ac.uk
• Raumonen, Mathematics, Tampere University, FI-33101 Tampere, Finland https://orcid.org/0000-0001-5471-0970 E-mail: pasi.raumonen@tuni.fi
• Krishna Moorthy, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium https://orcid.org/0000-0002-6838-2880 E-mail: Sruthi.KrishnaMoorthyParvathi@ugent.be
• Calders, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium https://orcid.org/0000-0002-4562-2538 E-mail: kim.calders@ugent.be
• Gielen, PLECO – Plants and Ecosystems, Faculty of Science, Antwerp University, Universiteitsplein 1, B-2610 Wilrijk, Belgium https://orcid.org/0000-0002-4890-3060 E-mail: bert.gielen@uantwerpen.be
• Verbeeck, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium https://orcid.org/0000-0003-1490-0168 E-mail: hans.verbeeck@ugent.be