Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning

By Xinlian Liang, Paula Litkey, Juha Hyyppä, Harri Kaartinen, Mikko Vastaranta, Markus Holopainen. IEEE Transactions on Geoscience and Remote Sensing, 2012

305 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/e23c2e1eb63aaef6d2a6f022ec5376ea2a179985

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Citations in the corpus

Stem biomass estimation based on stem reconstruction from terrestrial laser scanning point clouds (2013, methodology): “More details on the robust modelling procedure have been provided by Liang et al. (2012).”
Individual tree detection from Unmanned Aerial Vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest (2017, methodology): “[89] used eight different ITD detection algorithms on airborne LiDAR data of different forest types of Alpine Space and automatically matched the ITD results to forest inventory data.”
Estimation of Tree Stem Attributes Using Terrestrial Photogrammetry with a Camera Rig (2016, unknown): “Tree detection methods have been developed that detect trees in the point clouds resulting from either a single scan [6,7], co-registration of multiple scans [8,9] or from scans obtained by personal laser scanning (PLS) with portable units [10].”
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (2013, background): “To determine the tree components, the trunk is first defined approximately as a set Trunk of all those cover sets that are parallel to the approximated trunk direction and are two-dimensional (see also [9,25]).”
SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds (2015, methodology): “[26] were utilized to detect changes in the forest structure over time in Liang et al.”
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; ”
Outlook for the Next Generation’s Precision Forestry in Finland (2014, background): “MLS or TLS have already proven to be capable of measuring various structural tree parameters, such as DBH, height, stem curve, and tree species [25].”