Multiresolution Assessment of Forest Inhomogeneity
The spatial distribution of dominant tree species in an undisturbed mature stand tends to be regular and even, often exhibiting less variation than a simple Poisson model would suggest; in contrast the spatial distribution of species in a recovering or transitional stand would be expected to display considerable spatial variation. This paper studies the spatial distribution of hickory trees within the Bormann research plot of Duke Forest in an attempt to assess the degree of variation, as an indicator for forest maturation, using models recently introduced in Wolpert and Ickstadt (1995). A data augmentation scheme and Markov chain Monte Carlo methods are employed to evaluate Bayesian posterior distributions.
KeywordsMarkov Chain Monte Carlo Forest Maturation Markov Chain Monte Carlo Method Gaussian Random Field Random Field Model
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