A Proposal for a Forest Digital Twin Framework and Its Perspectives

Abstract

The increasing importance of forest ecosystems for human society and planetary health is widely recognized, and the advancement of data collection technologies enables new and integrated ways for forest ecosystems monitoring. Therefore, the target of this paper is to propose a framework to design a forest digital twin (FDT) that, by integrating different state variables at both tree and forest levels, creates a virtual copy of the forest. The integration of these data sets could be used for scientific purposes, for reporting the health status of forests, and ultimately for implementing sustainable forest management practices on the basis of the use cases that a specific implementation of the framework would underpin. Achieving such outcomes requires the twinning of single trees as a core element of the FDT by recording the physical and biotic state variables of the tree and of the near environment via real–virtual digital sockets. Following a nested approach, the twinned trees and the related physical and physiological processes are then part of a broader twinning of the entire forest realized by capturing data at forest scale from sources such as remote sensing technologies and flux towers. Ultimately, to unlock the economic value of forest ecosystem services, the FDT should implement a distributed ledger-based on blockchain and smart contracts to ensure the highest transparency, reliability, and thoroughness of the data and the related transactions and to sharpen forest risk management with the final goal to improve the capital flow towards sustainable practices of forest management.

Toward a Unified TreeTalker Data Curation Process

“…This reasoning showed us the opportunity to develop an open-source toolbox implementing a unified processing workflow for the broad deployment of TreeTalkers (Nature 4.0 SB srl) data within the scientific community. As already demonstrated by the ICOS project in the context of GHG emissions, the presented workflow will support data-sound model development and the inference of forest attributes through the integration of TreeTalker data with complementary data streams [10] and their ultimate feeding into artificial intelligence systems for forestry applications and, eventually, for their contribution to the creation of forest digital twins [20].…”

Mangrove Tree Density Detector using YOLO Based on Darknet Framework using RGB Drone Imagery

“…Similar to the research conducted by Moztarzadeh et al [28] to scan body parts for health analysis. Buonocore et al [29] proposed a framework for creating a Forest Digital Twin (FDT), which integrates various types of data from satellite imagery and IoT devices. Their approach involves twinning individual trees by integrating real-virtual digital interfaces to capture a wide array of physical, biotic, and environmental variables.…”

“…Environment monitoring also needs to be done frequently, which will increase the cost and time needed even more [8] [9]. [21] Yes No Ground 360°Cam No YOLOv2 Luo et al [22] Yes Yes RGB Drone No Faster R-CNN Donmez et al [23] Yes No RGB Drone No CCL Algorithm Mubin et al [24] Yes No RGB Sattelite No CNN LeNet Beloiu et al [25] Yes Yes Aerial Imagery No Faster R-CNN Pu et al [26] Yes Yes LiDAR Drone No LiDAR Analysis Jemaa et al [27] Yes No RGB Drone No YOLO Buonocore et al [29] No Based on the mentioned problems, in this research, we propose a system for mangrove density health system. In the era of emerging technology, there are more and more systems that can aid or replace human tasks for gathering data.…”

SWIFT: Simulated Wildfire Images for Fast Training Dataset

“…This method was evaluated for around 1.4 thousand trees, showing a high accuracy compared to existing methods. Buonocore et al [37] also introduced a framework for designing digital forest twins. They integrated various state variables at the forest and tree levels to generate a virtual forest copy.…”