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Introducing tree neighbouring relationship factors in forest pattern spatial analysis: weighted Delaunay triangulation method
Journal of Forestry Research ( IF 3 ) Pub Date : 2021-01-05 , DOI: 10.1007/s11676-020-01289-2
Jianjun Li , Kaiwen Zhu , Shuai Liu , Dan Li , Gui Zhang , Xing Liu , Weiming Yang

It is important to quantify and analyze forest spatial patterns for studying biological characteristics, population interaction and the relationship between the population and environment. In this study, the forest spatial structure unit was generated based on the Delaunay triangulation model (DTM), and the weights were generated using the comprehensive values of the tree diameter at breast height, total height and crown width. The distance between neighbors determined by the DTM was weighted to transform the original coordinates of trees into logical coordinates. Then, a weighted spatial pattern (WSP) was developed. After weighting, the neighboring trees were replaced, the replacement ratio was 38.3%, and there was 57.4% of the central tree. Correlation analysis showed that the uniform angle index of the WSP was significantly correlated with the tree size standard deviation under uniformity (r = 0.932) and randomness (r = 0.711). The DTM method not only considers the spatial distance between trees, but also considers the non-spatial attributes of trees. By changing the spatial topological relation between trees, this method further improves the spatial structure measurement of forest.



中文翻译:

在森林格局空间分析中引入树木相邻关系因子:加权Delaunay三角剖分方法

量化和分析森林空间格局对于研究生物学特征,种群相互作用以及种群与环境之间的关系非常重要。在这项研究中,森林空间结构单位是根据Delaunay三角剖分模型(DTM)生成的,权重是使用树木直径在胸高,总高和树冠宽度的综合值生成的。DTM确定的邻居之间的距离经过加权,以将树的原始坐标转换为逻辑坐标。然后,开发了加权空间模式(WSP)。加权后,对相邻树进行了替换,替换率为38.3%,中间树为57.4%。r  = 0.932)和随机性(r  = 0.711)。DTM方法不仅考虑树木之间的空间距离,而且考虑树木的非空间属性。通过改变树木之间的空间拓扑关系,该方法进一步改善了森林的空间结构度量。

更新日期:2021-01-06
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