Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data

By Erik Næsset. 2002

1,470 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/cc326eb22ea072151ae66bb28bdc2b41e2cab3fb

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In Environmental Engineering

In Insect Science

In Nature and Landscape Conservation

Citations in the corpus

Living and dying in a multi‐predator landscape of fear: roe deer are squeezed by contrasting pattern of predation risk imposed by lynx and humans (2014, methodology): “The method has been used to estimate forest parameters such as tree height and stem volume successfully (Næsset 2002).”
Characterizing forest structural types and shelterwood dynamics from Lorenz-based indicators predicted by airborne laser scanning (2013, methodology): “A widely used area-based method consists of computing ALS metrics from the height distributions observed both at the plot area and throughout a grid of similarly sized cells covering the whole area surveyed (Næsset 2002; McGaughey 2012).”
Estimating percentile-based diameter distributions in uneven-sized Norway spruce stands using airborne laser scanner data (2007, methodology): “Næsset (2002, 2004b) concluded that all the stand parameters mentioned above can be estimated with higher precision by means of laser scanner data than by conventional field-based methods.”
Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data (2009, background): “…(Lefsky et al., 1999; Næsset, 2002; Lim et al., 2003a; Holmgren, 2004; Jensen et al., 2006), bole diameter at breast height (Lefsky et al., 1999; Næsset 2002; Lim et al., 2003a; Jensen et al., 2006; Anderson et al., 2008), and wood volume or biomass (Lim et al., 2003a; Lim & Treitz, 2004;…”
Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements (2013, background): “, 2005); and especially in forestry applications (Lefsky et al., 1999; Næsset, 2002; Maltamo et al., 2006; Popescu, 2007; Estornell et al., 2011).”
Inventory of Small Forest Areas Using an Unmanned Aerial System (2015, methodology): “Compared with the results of previous studies conducted in the same area but at a larger scale using ALS or Ultracam XP data [31,54], the main differences are that the current study shows that the hdom model had a higher adj.”
Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland (2013, result): “…shown similar (Maltamo et al. 2004; Uuttera et al. 2006) or improved accuracy (Suvanto et al 2005; Uuttera et al. 2006; Peuhkurinen et al. 2011; Næsset (2002) compared with the conventional visual assessment of the stand characteristics or photo-interpretation (Kangas et al 2004; Uuttera et…”
Predicting wood quantity and quality attributes of balsam fir and black spruce using airborne laser scanner data (2014, methodology): “Most operational ALS inventories have used area-based approaches involving the development of models to predict attributes of interest for individual cells of a grid (Næsset, 2002).”
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 (2003, background): “For example, a number of authors (e.g., Lefsky, Harding, et al., 1999; Magnussen & Boudewyn, 1998; Næsset, 2002; Ni-Meister, Jupp, & Dubayah, 2001) have investigated the possibility of extracting information about the vertical structure of the canopy per stand or sample plot, as well as aboveground ”