Modelling the diameter distribution of Pinus sylvestris, Pinus nigra and Pinus halepensis forest stands in Catalonia using the truncated Weibull function

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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 diameter distributions of Betula alba L. stands in Northwest Spain with the two-parameter Weibull function (2007, methodology): “Palahí et al. (2006a) developed parameter prediction models for Pinus sylvestris, Pinus nigra and Pinus halepensis in Catalonia using the truncated Weibull function.”
Characterization of diameter distribution data in near-natural forests using the Birnbaum–Saunders distribution (2008, methodology): “(1988) was, for example, used to estimate the degree of fit of distributions in mixed stands (Zhang et al. 2003; Palahı́ et al. 2006; Podlaski 2006) and during modeling of DBH distributions (Cao and Baldwin 1999).”
Evaluation of methods to predict Weibull parameters for characterizing diameter distributions (2013, background): “…et al. 1984, Baldwin and Feduccia 1987), longleaf pine (Lohrey and Bailey 1977, Jiang and Brooks 2009), loblolly and slash pine (Brooks et al. 1992), Scots pine, Austrian pine, and Pinus halepensis (Palahi et al. 2006), birch (Gorgoso-Varela et al. 2007), and black poplar (Andrasev et al. 2009).”