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

Author:

Li Wanlu12,Yang Meng12,Xi Benye3ORCID,Huang Qingqing4

Affiliation:

1. School of Information Science and Technology, Beijing Forestry University (BFU), Qinghua East Road 35, Haidian District, Beijing 100083, China

2. Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration, Beijing 100083, China

3. Ministry of Education Key Laboratory of Silviculture and Conservation, Beijing Forestry University (BFU), Qinghua East Road 35, Haidian District, Beijing 100083, China

4. School of Technology, Beijing Forestry University (BFU), Qinghua East Road 35, Haidian District, Beijing 100083, China

Abstract

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.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Forestry

Reference56 articles.

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