Weibull and percentile models for lidar-based estimation of basal area distribution

By Terje Gobakken, Erik Næsset. 2005

94 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/96ef5d4e4013ea797aeccded6ab229882f176b95

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In Environmental Engineering

In Insect Science

In Nature and Landscape Conservation

Citations in the corpus

Non-parametric prediction of diameter distributions using airborne laser scanner data (2009, methodology): “The error indices proposed by Reynolds et al. (1988), later applied by numerous other authors (e.g. Gobakken & Næsset, 2005; Palahı́ et al., 2006; Kangas et al., 2007; Newton & Amponsah, 2007; Packalén & Maltamo, 2008), were also used.”
Modelling tree size diversity from airborne laser scanning using canopy height models with image texture measures (2013, background): “Many studies have now demonstrated the value and precision of ALS for estimating tree size variables (diameter, height or basal area) and their frequency distributions; a number of modelling techniques have been evaluated from conifer, broadleaf and mixed forest stands (Maltamo et al., 2004,2007; Go”
Estimation of tree lists from airborne laser scanning by combining single-tree and area-based methods (2010, methodology): “A comparison of a Weibull DBH distribution and DBH percentiles showed no significant difference between the two validated methods (Gobakken and Næsset 2005).”
A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing (2011, methodology): “…of tree crowns, research 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.…”
Capturing tree crown formation through implicit surface reconstruction using airborne lidar data (2009, unknown): “…et al., 2004), detection of single or multi-story stand condition (Zimble et al., 2003), estimation of carbon density (Patenaude et al., 2004), biomass estimation (Bortolot & Wynne, 2005), and modeling the distribution of understory vegetation (Gobakken & Næsset, 2004, 2005; Maltamo et al., 2004).”