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Sustainable Urban Forest using Multiple Regression Models

机译：使用多元回归模型的可持续城市森林

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Global Warming and carbon sequestration have expedited the urgency of proper forest management and its practices. This sustainability comes with stringent environmental policies, planning and management. With increased pressure for better and quality urban living, the existence of well-managed urban forest is of prime importance where the need for human recreational activities, balanced natural ecosystem and habitat, as well as the oxygen and carbon cycle, have to be sustained. Since, the green canopy is directly related to the bole and tree volume, urban forests sustainability can be mathematically modeled using multiple regressions. The Multiple Regression (MR) models are based on the tree-stem mensuration data. Three volumetric formulas are used to calculate the tree stem volume, namely, the Newton, Huber and Smalian equations. Data are collected and categorized according to sizes: small (S), medium (M) and large (L). Six independent variables based on measurable variables and five categorical variables based on location samples have been taken. Data transformations are done for normality and Spearman correlation coefficient matrix is used to identify bivariate relationships between them. Removal of high multicollinearity and insignificant variables and applying parameter tests are done on the models. Three selected best volumetric models from the equations are chosen based on the eight selection criteria (8SC). Comparisons are made to have the best model equation. The Newton?s MR models on all the three sizes are found to be the best to represent the mensuration growth factors which affect the sustainability of the urban forests.
机译：全球变暖和碳固存加快了适当森林管理及其实践的紧迫性。这种可持续性伴随着严格的环境政策，规划和管理。随着改善更好和高质量城市生活的压力增加，在必须维持人类娱乐活动，平衡自然生态系统和栖息地以及氧气和碳循环的需求的情况下，管理良好的城市森林的存在至关重要。由于绿色的树冠与树干和树木的体积直接相关，因此可以使用多元回归来对城市森林的可持续性进行数学建模。多元回归（MR）模型基于树柄确定数据。使用三个体积公式来计算树的茎体积，即牛顿，Huber和Smalian方程。数据根据大小（小（S），中（M）和大（L））进行收集和分类。基于可测量变量的六个自变量和基于位置样本的五个分类变量。对正态性进行数据转换，并使用Spearman相关系数矩阵来识别它们之间的双变量关系。在模型上去除了较高的多重共线性和无关紧要的变量，并进行了参数测试。基于八个选择标准（8SC）从方程中选择了三个选择的最佳体积模型。进行比较以获得最佳模型方程式。发现所有三种尺寸的牛顿MR模型都是最好的代表影响城市森林可持续性的测定增长因子。

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