Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models
By Christian Salas, Liviu Theodor Ene, Timothy G. Gregoire, Erik Næsset, Terje Gobakken. 2010
102 citations recorded by the source corpus.
Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/28f78bf56174292a1d01c945ca4127e0f676b23e
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In Environmental Engineering
In Insect Science
In Nature and Landscape Conservation
Citations in the corpus
- Above-Ground Biomass and Biomass Components Estimation Using LiDAR Data in a Coniferous Forest (2013, background): “These physical characteristics, including tree height, crown diameter, and crown shape correlate with biomass, and may be regressed against either diameter at breast height (DBH) or biomass to obtain general LiDAR-biomass models [2–10].”
- Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data (2011, methodology): “It has been applied successfully for measuring and monitoring vegetation structural data across the landscape (Popescu & Wynne, 2004; Reutebuch et al., 2005; Salas et al., 2010).”
- Links, comparisons and extensions of the geographically weighted regression model when used as a spatial predictor (2011, unknown): “In contrast, GWR has been empirically and unfavourably compared to: (a) alternative regressions (Wheeler and Waller 2009; Salas et al. 2010) or (b) kriging (Lloyd 2010).”