Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America

By Tomas Brandtberg. 2003

479 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/6989d48f6710b9d215e6d2a40436cae762b3a274

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In Environmental Engineering

In Insect Science

In Nature and Landscape Conservation

Citations in the corpus

Estimation of tree lists from airborne laser scanning by combining single-tree and area-based methods (2010, background): “A mixture of tree species within field plots is also a motivation for tree crown segmentation because tree species information may be derived from the tree crown segments (Brandtberg et al. 2003, Holmgren and Persson 2004, Holmgren et al. 2008).”
A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing (2011, background): “…mean tree height, stem volume and biomass at stand level (e.g. Næsset 2002, Gobakken and Næsset 2005, Maltamo et al. 2006), or for extracting individual tree-based information such as crown diameter and tree height (e.g. Brandtberg et al. 2003, Holmgren and Persson 2004, Chen et al. 2006).”
Review of optical-based remote sensing for plant trait mapping (2013, methodology): “Discrete 428 return laser scanning have been successfully used for height estimation mainly of tall canopies 429 such as boreal coniferous (Hopkinson et al., 2004; Næsset et al., 2004), temperate deciduous 430 (Brandtberg et al., 2003) or tropical (Clark et al., 2004) forests.”
Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data (2008, background): “Conversely, sufficient LiDAR pulse energy is reflected off the top of deciduous canopies during leaf-off conditions to distinguish individual tree crowns (Brantberg et al., 2003).”
Three-dimensional surface reconstruction of tree canopy from lidar point clouds using a region-based level set method (2013, methodology): “salient features) for segmentation and tree species classification when the previous models are applied to obtain the tree height, crown width, basal area, crown base height, and crown volume using lidar data (Brandtberg et al. 2003; Koch, Heyder, and Weinacker 2006; Lee and Lucas 2007; Reitberger e”
An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning (2012, methodology): “This was immediately followed by standwise mean height and volume estimation [14–16], based on the data collected via ranging measurements, and very soon ALS was applied to inventorying, focusing on individual trees [17–20] with the advent of rapid image processing, tree species classification [21,2”
Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data (2012, methodology): “from Breidenbach et al. (2010) made an attempt to compensate for the non-detected trees by connecting non-detected trees in the field data to nearby segments and got good results.”