Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar

By Fumiki Hosoi, Kenji Omasa. IEEE Transactions on Geoscience and Remote Sensing, 2006

398 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/5d77d5723ef92ed2dd96901190399269b4dc2796

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Citations in the corpus

Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements (2013, methodology): “A volumetric pixel (voxel) is the minimum discrete volume that can be processed in a tridimensional object (Hosoi and Omasa, 2006).”
Rapid measurement of the three-dimensional distribution of leaf orientation and the leaf angle probability density function using terrestrial LiDAR scanning (2017, background): “…with the camera view direction.52 Terrestrial LiDAR scanning, which is the focus of this paper, has seen in-53 creasing usage in obtaining measurements of canopy structure (e.g., Radtke and54 Bolstad, 2001; Henning and Radtke, 2006; Hosoi and Omasa, 2006; Rosell et al.,55 2009; Yang et al., 2013).”
Retrieving the gap fraction, element clumping index, and leaf area index of individual trees using single-scan data from a terrestrial laser scanner (2017, methodology): “LAI retrieval approaches based on TLS can be categorized into two groups: voxel-based methods using data from multiple scans (Hosoi and Omasa, 2006; Van der Zande et al., 2006) and point-based methods using data from a single scan (Danson et al.”
3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar (2013, methodology): “D point cloud data for parts occluded by other branches, surrounding trees, and understory) which causes estimates of tree structural properties to be inaccurate (Côté et al., 2009, 2011; Dassot et al., 2011; Delagrange and Rochon, 2011; Hosoi and Omasa, 2007).”
Canopy clumping appraisal using terrestrial and airborne laser scanning (2015, background): “…and vertical distribution of vegetation terrestrial and airborne laser scanning, Remote Sensing of Environment canopy, although most studies have focused on the LAI estimation (Garcia et al., 2012; Hopkinson et al., 2013; Hosoi & Omasa, 2006; Strahler et al., 2008) and very few have addressed Ω.”
Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors (2009, background): “Particularly, terrestrial LiDAR, with very high density point clouds, allows for improved retrieval of forest stand structure information including LAI [34,35].”
International benchmarking of terrestrial laser scanning approaches for forest inventories (2018, background): “The past two decades have witnessed steady progress in these types of studies (Henning and Radtke, 2006; Hosoi and Omasa, 2006; Lefsky and McHale, 2008; Maas et al., 2008; Strahler et al., 2008; Côté et al., 2009; Jupp et al., 2009; Tansey et al., 2009).”
The leaf angle distribution of natural plant populations: assessing the canopy with a novel software tool (2015, background): “Only a few studies focus on a quantitative assessment of leaf orientations of the outer canopy layers of plants grown under field conditions [21-23].”
Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning (2018, methodology): “This method does not take into account the azimuth angle because it assumes that leaves are uniformly distributed with respect to the azimuth (Hosoi and Omasa, 2006).”
Estimation of 3D vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters (2017, methodology): “For example, Hosoi and Omasa (2006) introduced a leaf inclination correction to compute LAI for a single tree (Voxel-based Canopy Profiling) to take into account the non-random orientation of leaves.”