Imputing tree-lists from aerial attributes for complex stands of south-eastern British Columbia
By By H Temesgen, V. LeMay, K. Froese, P. Marshall. 2003
64 citations recorded by the source corpus.
Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/ffdee818e1d08c476610950430756b44ce106934
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Ronald E. McRoberts
- Erkki Tomppo
- Aaron Weiskittel
- John A. Kershaw
- Jerome K. Vanclay
- D. Hann
- Hailemariam Temesgen
- Jeffrey Scott Evans
In Insect Science
In Nature and Landscape Conservation
- Ronald E. McRoberts
- Erkki Tomppo
- Aaron Weiskittel
- John A. Kershaw
- Jerome K. Vanclay
- D. Hann
- Hailemariam Temesgen
- Jeffrey Scott Evans
Citations in the corpus
- Comparison of Nearest Neighbor Methods for Estimating Basal Area and Stems per Hectare Using Aerial Auxiliary Variables (2005, background): “…and used to estimate the missing Y values, some estimates may not be within the realm of real values (e.g., averaging one reference stand with species 1 and 2, with another of species 2 and 3, results in an average with three species, a combination that may not exist; Temesgen et al. 2004).”
- Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery (2009, methodology): “…forest inventory applications including imputing values for missing observations in inventory databases (LeMay & Temesgen, 2005; Moeur & Stage,1995; Temesgen et al., 2003), mapping forest attributes using the spectral values of satellite imagery (Franco-Lopez et al., 2001; McRoberts et al., 2007),…”
- Forest Growth and Yield Modeling (2011, methodology): “…classification 292 CH 14 MODEL CONSTRUCTION and regression trees (CART; Nigh and Love, 2004; Fan et al., 2006; R€aty and Kangas, 2008), generalized additive models (GAMs; Zhang et al., 2008; Aertsen et al., 2010), and k-nearest neighbor methods (k-NN; Temesgen et al., 2003; Sironen et al., 2008).”
- Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data (2008, background): “…algorithms can provide predictions of timber volume (Mäkelä & Pekkarinen, 2004), basal area (FrancoLopez et al., 2001; LeMay & Temesgen, 2005), stems per hectare (LeMay & Temesgen, 2005), timber yield (Maltamo & Eerikäinen, 2001), and species-level forest inventory data (Temesgen et al., 2003).”