Estimation of stem volume using laser scanning-based canopy height metrics

By Matti Maltamo, Kalle Eerikäinen, Petteri Packalen, Juha Hyyppä. 2006

196 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/4581f5cfa5cfac40ebeec4bb0e1313817dd3f30e

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In Ecology

In Environmental Engineering

In Nature and Landscape Conservation

Citations in the corpus

AN INVESTIGATION OF EFFECTIVENESS OF SIMULATION IN DEVELOPING ORAL SKILLS: A CASE STUDY (2013, unknown): “407 approaches (Maltamo et al. 2006).”
Effects of pulse density on predicting characteristics of individual trees of Scandinavian commercial species using alpha shape metrics based on airborne laser scanning data (2008, methodology): “There are also a few other studies considering the effects of pulse density on plot-level assessments of forest structure (Holmgren, 2004; Lovell et al., 2005; Maltamo et al., 2006; Magnusson et al., 2007; Gobakken and Næsset, 2007).”
Estimation of tree lists from airborne laser scanning by combining single-tree and area-based methods (2010, methodology): “…boreal forests because they produce estimates of mean tree height, mean DBH, basal area and stem volume with errors of the same size as from accurate field inventories (i.e. using several field plots within each forest stand) (Næsset and Bjerknes 2001, Næsset et al. 2005, Maltamo et al. 2006).”
Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities (2012, background): “…prediction of some variables such as mean and dominant height, quadratic mean diameter, stand basal area, stand volume or stand aboveground biomass (Maltamo et al., 2006; Gobakken and Næsset, 2007; Stephens et al., 2007; Treitz et al., 2010) when the point cloud was reduced between 94.4 and 95.3…”
Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia (2007, methodology): “On a more local scale, procedures for stand-level forest inventory following a wall-to-wall approach based on scanning lasers have been developed over the past 5 10 years (Næsset, 1997, 2002; Means et al., 2000; Holmgren, 2004; Maltamo et al., 2006) and have been in operational use since 2002 (Næsse”
Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements (2013, background): “…such as: hydraulic modeling (Cobby et al., 2001); building representation (Hermosilla et al., 2011); changes in beach sand volumes (Shrestha et al., 2005); and especially in forestry applications (Lefsky et al., 1999; Næsset, 2002; Maltamo et al., 2006; Popescu, 2007; Estornell et al., 2011).”
Non-parametric prediction of diameter distributions using airborne laser scanner data (2009, methodology): “…methods (Maltamo et al., 2007; Mehtätalo et al., 2007; Breidenbach et al., 2008), (3) applications in boreal forest reserves, i.e. in areas with a great variety of distribution forms (Maltamo et al., 2006a; Bollandsås & Næsset, 2007), and (4) preharvest measurements (Peuhkurinen et al., 2008).”
The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning (2013, result): “area, and volume [14,57] it is not surprising that the predictions based on the image-based metrics in these studies are similar to those generated from the ALS metrics (Table 4).”
A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing (2011, methodology): “…has utilized LiDAR measurements for estimating 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,…”