Predicting product recovery accurately from Jack pine inventory measurements

背景：从森林清查中估计的木材量长期以来一直用于制定各种森林管理政策/决策。众所周知，每立方米的木材在产品回收方面并不是平等的。因此，为了作出更明智的森林管理和最终用途决定，有必要直接从森林清查中估计产品恢复情况。利用采油树的三维几何数据可以准确估计采油树的采收率。然而，使用库存数据来描述杆的三维几何形状是不可能的。因此，本项目提出了一种原创和创新的方法，作为应对这一挑战的替代方案。总体目标：该项目是开发一个木材恢复校正模型的茎变形，以估计产品恢复直接和准确地从森林清查。方法：该工作将在5年内分2个阶段完成：1)实形和虚拟树干的锯切仿真与优化，并对两种类型的树干与树木和林分特征之间的木材恢复差异关系进行数学建模；2)对两种类型的树干进行分析，建立两种类型的树干形态与木材恢复差异与树龄之间的关系。新知识/好处：项目首先将有助于HQP的培训。它将填补我们在两种类型的茎之间的木材恢复差异的知识空白，以及它们与树/林分特征的关系。因此，可以首次建立杆的变形校正模型。该模型将允许根据森林清查数据准确地估计产品回收率。因此，可以根据所获得的产品回收知识做出各种森林管理决策，以实现木材量以外的特定目标。森林资源的虚拟加工还将有助于优化造林规划和采伐时间表，以实现资源价值最大化，并更好地满足特定产品的制造和市场需求。

BACKGROUND: Wood volume estimated from forest inventory has long been used to develop/make various forest management policies/decisions. It is well-known that each m3 of wood is not created equally in terms of product recovery. To make better informed forest management and end-use decisions, it is therefore necessary to estimate product recovery directly from forest inventory. Product recovery from a tree can be estimated accurately with 3-D stem geometrical data. However, it is not possible to describe 3-D stem geometry with stem deformation using inventory data. Therefore, this project proposes an original and innovative approach as an alternative to addressing this challenge. OVERALL OBJECTIVE: The project is to develop a lumber recovery correction model for stem deformations to estimate product recovery directly and accurately from forest inventory. APPROACH: The work will be completed in 5 years in 2 phases: 1) sawing simulation & optimization for real-shape and virtual stems & mathematical modeling of the relationships of lumber recovery differences between the two types of stems with tree and stand characteristics, 2) stem analysis and establishment of the relationship of stem form and lumber recovery differences between the two types of stems with tree age. NEW KNOWLEDGE/BENEFITS: The project first of all will contribute to the training of HQP. It will fill the gap in our knowledge of the lumber recovery differences between two types of stems, and their relationships with tree/stand characteristics. Thus, a correction model for stem deformations could be developed for the first time. The model will allow to estimate product recovery accurately from forest inventory data. Therefore, various forest management decisions can be made based on the acquired knowledge of product recovery to achieve specific objectives beyond wood volume. The virtual processing of the forest resource will also help optimize silvicultural planning and harvesting schedules to maximize the resource value, and to better meet manufacturing and market requirements for specific products.