Automatic forest inventory parameter determination from terrestrial laser scanner data

By Hans-Gerd Maas, A. Bienert, S. Scheller, Enda Keane. 2008

449 citations recorded by the source corpus.

Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/9aa183dcc52012053099970de4a08730a34ae7c5

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In Environmental Engineering

In Insect Science

In Nature and Landscape Conservation

Citations in the corpus

International benchmarking of terrestrial laser scanning approaches for forest inventories (2018, background): “For example, the rate of correctly extracted trees has ranged from 20% to 100% (Thies and Spiecker, 2004; Maas et al., 2008; Strahler et al., 2008; Brolly and Kiraly, 2009; Murphy et al., 2010; Lovell et al., 2011; Yao et al., 2011; Liang et al., 2012; Lindberg et al., 2012; Liang and Hyyppä, 2013; ”
Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning (2017, background): “However, one reference [44] reported extraordinary high detection rates between 86.”
Individual tree detection from Unmanned Aerial Vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest (2017, background): “[86] conducted numerous pilot studies using terrestrial LiDAR and reported that more than 97% of the trees could be detected correctly.”
Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning (2012, methodology): “In previous studies on stem locating in TLS data, the proportions of located stems from single- and multiscan data have been 22% and 52% within a plot with 556 stems/ha [18], respectively; 97% within plots with an average density of 321 stems/ha and 100% within a plot with 310 stems/ha [19].”
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (2013, methodology): “Modeling procedures fulfilling all the conditions above have hitherto not been available, although various methods have been developed to allow automated tree reconstruction [10,15–20].”
Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories (2018, methodology): “By placing cylinders into the detected tree positions, an automated tree segmentation can be achieved [5,9].”
Estimation of stem attributes using a combination of terrestrial and airborne laser scanning (2012, methodology): “…positions and diameters using either manual detection (Hopkinson et al. 2004), a clustering algorithm (Bienert et al. 2007; Király and Brolly 2007; Maas et al. 2008), skeletonization (Gorte and Pfeifer 2004), or the Hough transform (Aschoff et al. 2004), and then fit circles along the tree stems…”
Stem biomass estimation based on stem reconstruction from terrestrial laser scanning point clouds (2013, background): “…al. 2008, Strahler et al. 2008), tree height and diameter at breast height (DBH) (Hopkinson et al. 2004, Thies et al. 2004, Watt and Donoghue 2005, Henning et al. 2006a, 2006b, Maas et al. 2008), for assessing gap fraction (Strahler et al. 2008) and for mapping stem positions (Liang et al. 2011).”