Data underlying the MSc thesis: Geometrical Mangrove Models: Quantifying frontal surface area distribution for Avicennia marina vegetation

In this study, manual measurements were performed to obtain tree structure parameters. Both canopy and root measurements were conducted for Avicennia marina vegetation with varying characteristics (age and density). After that, we developed a search tree algorithm to loop through all tree data, compute parameters of interest and store the results in assigned data arrays. Parameters of interest to obtain after the data analysis were branch dimensions and diameter ratios of branches (between various branch classes). This information was necessary to create a blueprint for constructing geometrical tree models. Tree modelling started with the construction of a root (pneumatophore) model. Additionally, the frontal surface area of these roots was computed and displayed as a function of the height. In addition to the root model, we constructed two canopy models. The first model is based on relations between branches and can be called deterministic or dependent (canopy model 1). The second canopy model (canopy model 2) generates branch dimensions based on the normal distribution of branch diameters and is, therefore, more probabilistic with branches independent of each other.

本研究通过人工测量获取林木结构参数。针对不同生长特征（树龄与密度）的白骨壤（Avicennia marina）植被，分别开展冠层与根系的测量工作。随后，本研究开发了搜索树算法，遍历全部林木数据集，计算目标参数并将结果存储至指定数据数组中。本次数据分析所需获取的目标参数包括枝条尺寸以及不同枝条等级间的枝条直径比值。上述信息可为构建几何林木模型提供设计蓝图。林木建模首先从根系（呼吸根）模型的构建入手。此外，本研究还计算了该类根系的正面表面积，并将其表征为树高的函数进行展示。除根系模型外，本研究还构建了两类冠层模型。第一类模型基于枝条间的关联关系构建，可称为确定性关联模型（冠层模型1）。第二类冠层模型（冠层模型2）则基于枝条直径的正态分布生成枝条尺寸，因此其枝条间相互独立，更具概率特性。