数字孪生虚拟人工林建模与数据分析框架,Forests

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数字孪生虚拟人工林建模与数据分析框架
Forests ( IF 2.4 ) Pub Date : 2023-03-26 , DOI: 10.3390/f14040683
Wanlu Li _{1,

2} , Meng Yang _{1,

2} , Benye Xi ₃ , Qingqing Huang ₄

Affiliation

通过人工播种和种植方式培育的人工林对人类社会具有重要意义。然而，这些森林的大多数试验地点都位于偏远地区。因此，深入开展异地森林经营管理和异地实验研究，可以更好地满足科研人员的实验和管理需求。本文以三倍体毛白杨实验人工林为基础，提出了一种虚拟杨人工林系统的数字孪生架构。该框架包括虚拟种植园建模和数据分析。针对这一体系架构，本文从理论上分析了物理世界、数字世界和其中包含的研究者三大主体，以及它们之间的交互机制。对于虚拟种植园建模，采用了基于激光雷达点云数据的树木建模方法。提出了过渡粒子流法与AdTree方法结合建树，并与其他模型进行集成优化。对于人工林数据分析，建立了基于森林监测数据的数据库。树木生长方程是通过拟合树木胸径数据得出的，然后用于预测和模拟难以测量的直径相关数据的趋势。实验结果表明，基于该框架可以构建初步的数字孪生型杨树人工林系统。该系统由 2160 棵树和 10 种监测或预测数据的模拟组成，为数字孪生技术在林业领域的应用提供了新的实践依据。优化后的树模型内存消耗减少67%以上，而100多个数据项的树生长方程R2可达87%以上，大大提高了系统的性能和精度。因此，利用林业信息网络化和数字化支持人工林试验经营，有助于推进林业数字化转型，实现森林智慧经营模式。

"点击查看英文标题和摘要"

Framework of Virtual Plantation Forest Modeling and Data Analysis for Digital Twin

Plantation forests, cultivated through artificial seeding and planting methods, are of great significance to human society. However, most experimental sites for these forests are located in remote areas. Therefore, in-depth studies on remote forest management and off-site experiments can better meet the experimental and management needs of researchers. Based on an experimental plantation forest of Triploid Populus Tomentosa, this paper proposes a digital twin architecture for a virtual poplar plantation forest system. The framework includes the modeling of virtual plantation and data analysis. Regarding this system architecture, this paper theoretically analyzes the three main entities of the physical world, digital world, and researchers contained in it, as well as their interaction mechanisms. For virtual plantation modeling, a tree modeling method based on LiDAR point cloud data was adopted. The transitional particle flow method was proposed to combine with AdTree method for tree construction, followed by integration with other models and optimization. For plantation data analysis, a database based on forest monitoring data was established. Tree growth equations were derived by fitting the tree diameter at breast height data, which were then used to predict and simulate trends in diameter-related data that are difficult to measure. The experimental result shows that a preliminary digital twin-oriented poplar plantation system can be constructed based on the proposed framework. The system consists of 2160 trees and simulations of 10 types of monitored or predicted data, which provides a new practical basis for the application of digital twin technology in the forestry field. The optimized tree model consumes over 67% less memory, while the R2 of the tree growth equation with more than 100 data items could reach more than 87%, which greatly improves the performance and accuracy of the system. Thus, utilizing forestry information networking and digitization to support plantation forest experimentation and management contributes to advancing the digital transformation of forestry and the realization of a smart management model for forests.

更新日期：2023-03-26

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