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Modelling the spatial structure of forest stands by multivariate point processes with hierarchical interactions

机译:通过具有分层交互作用的多元点过程对森林林分的空间结构进行建模

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摘要

A stochastic model is applied to describe the spatial structure of a forest stand. We aim at quantifying the strength of the competition process between the trees in terms of interaction within and between different size classes of trees using multivariate Gibbs point processes with hierarchical interactions intro_duced in [H_gmander, H., S_rkk_, A., 1999. Multitype spatial point patterns with hierarchical interactions. Biometrics 55, 1051-1058]. The new model overcomes the main limitation of the' traditional use of the Gibbs models allowing to describe systems with non-symmetric interactions between different objects. When analyzing interactions between neighbouring trees it is natural to assume that the size of a tree determines its hierarchical level: the largest trees are not influenced by any other trees than the trees in the same size class, while trees in the other size classes are influenced by the other trees in the same class as well as by all larger trees. In this paper, we describe a wide range of Gibbs models with both hierarchical and non-hierarchical interactions as well as a simulation algorithm and a parameter estimation procedure for the hierarchical models. We apply the hierarchical interaction model to the analysis of forest data consisting of locations and diameters of tree stems.
机译:应用随机模型描述林分的空间结构。我们的目标是使用多变量吉布斯点过程和在[H_gmander,H.,S_rkk_,A.,1999.中引入的层次化交互作用],根据树木之间和不同大小类别之间的相互作用来量化树木之间竞争过程的强度。具有分层交互作用的点模式。生物识别55,1051-1058]。新模型克服了传统的Gibbs模型使用的主要局限性,该传统用法允许描述不同对象之间具有非对称交互作用的系统。在分析相邻树之间的交互时,自然会假设一棵树的大小决定了它的层次级别:除了相同大小级别的树以外,最大的树不受其他任何树的影响,而其他大小级别的树则受到影响。被同等级的其他树木以及所有较大的树木所覆盖。在本文中,我们描述了具有层次和非层次相互作用的各种Gibbs模型,以及用于该层次模型的仿真算法和参数估计过程。我们将层次交互模型应用于由树茎的位置和直径组成的森林数据分析。

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