Articles containing the keyword 'voxel'

Harvester-mounted mobile laser scanning (HarvMLS) is a novel approach to quantify forest structure in situ during harvesting operations. However, its reliability relative to established aerial and ground-based laser scanning systems remains unknown. In this study, we benchmarked HarvMLS against drone-based laser scanning (DLS) and backpack mobile laser scanning (BpMLS) for forest structure assessment. Point cloud data were acquired using these laser scanning systems in a boreal forest in southern Finland during thinning operations in 2024. HarvMLS collected data during thinning, while BpMLS and DLS collected data immediately before and after thinning. A grid-level approach was used for point cloud processing. Sixty-two 10 m × 10 m plots were analyzed, each with pre- and post-thinning data. Forest structure was characterised using estimates of structural attributes and complexity. The structural attributes included canopy height, canopy cover (CC), and filled voxel proportion (FVP). Structural complexity was quantified using the coefficient of variation (CV) of the structural attributes. Furthermore, FVP was analyzed across various canopy height classes to evaluate the scanning system’s capacity to capture vegetation density at different canopy layers. The scanning systems consistently estimated canopy height, CC, and the CV of these attributes, including the CV of FVP. Significant differences were detected for FVP and FVP at lower canopy layers (<15 m). However, post hoc tests showed no significant difference between HarvMLS and BpMLS. These findings indicate that HarvMLS provides reliable estimates of forest structural attributes and their variability during active forest operations.

• Kafle, School of Forest Sciences, University of Eastern Finland (UEF), Yliopistokatu 7, FI-80100 Joensuu, Finland https://orcid.org/0000-0003-0744-3480 E-mail: binod.kafle@uef.fi
• Kankare, Department of Geography and Geology, University of Turku, FI-20014 Turun yliopisto, Finland https://orcid.org/0000-0001-6038-1579 E-mail: viveka@utu.fi
• Kaartinen, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland https://orcid.org/0000-0002-4796-3942 E-mail: harri.kaartinen@nls.fi
• Väätäinen, Production systems, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-6886-0432 E-mail: kari.vaatainen@luke.fi
• Hyyti, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland https://orcid.org/0000-0003-4664-6221 E-mail: heikki.hyyti@nls.fi
• Faitli, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland https://orcid.org/0000-0001-5334-5537 E-mail: tamas.faitli@nls.fi
• Koivumäki, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland https://orcid.org/0000-0002-6307-1637 E-mail: niko.koivumaki@maanmittauslaitos.fi
• Hyyppä, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland E-mail: juha.coelasr@gmail.com
• Kukko, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (FGI), P.O. Box 84, FI-00521 Helsinki, Finland https://orcid.org/0000-0002-3841-6533 E-mail: antero.kukko@nls.fi
• Kärhä, School of Forest Sciences, University of Eastern Finland (UEF), Yliopistokatu 7, FI-80100 Joensuu, Finland E-mail: kalle.karha@uef.fi

• Lu, Deparment of Forestry, University of Missouri, Columbia, MO, USA E-mail: ml@nn.us
• Nygren, The Finnish Society of Forest Science, P.O. 18, FI-01301 Vantaa, Finland E-mail: pekka.nygren@metla.fi
• Perttunen, Finnish Forest Research Institute, Vantaa, Finland E-mail: jp@nn.fi
• Pallardy, Deparment of Forestry, University of Missouri, Columbia, MO, USA E-mail: sgp@nn.us
• Larsen, Deparment of Forestry, University of Missouri, Columbia, MO, USA E-mail: drl@nn.us

Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beams’ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our method’s output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.

• Schraik, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; https://orcid.org/0000-0002-7794-3918 E-mail: daniel.schraik@aalto.fi
• Hovi, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; https://orcid.org/0000-0002-4384-5279 E-mail: aarne.hovi@aalto.fi
• Rautiainen, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; Aalto University, School of Electrical Engineering, Department of Electronics and Nanoengineering, P.O. Box 14100, FI-00076 Aalto, Finland https://orcid.org/0000-0002-6568-3258 E-mail: miina.a.rautiainen@aalto.fi