Digital Twins Bring High-Resolution Forest Structure to Management

Forestry technology is increasingly embracing digital innovation, and one of the latest developments involves creating high-resolution digital models of forests. Known as forest digital twins, these models replicate the structure of real forest stands, providing new insights for management, monitoring, and sustainability planning.

Using terrestrial laser scanning (TLS) instruments, researchers and forestry specialists can now map individual trees in unprecedented detail. Unlike satellite or aerial imagery, TLS scans from the ground allow measurement of tree trunks, branches, and crowns with millimeter accuracy. These measurements are compiled into three-dimensional digital models that capture the spatial layout, height, diameter, and canopy structure of every tree in a stand.

These forest digital twins have several applications in modern forestry. They allow managers to observe how tree spacing, canopy density, and branch structure influence sunlight penetration, growth patterns, and habitat diversity. The models also help track forest disturbances, whether from storms, pests, or harvesting, and monitor how ecosystems recover over time.

Benefits for Forest Management

• Precision planning: Digital twins provide detailed structural information that can improve decisions on thinning, selective harvesting, and restoration.
• Carbon and ecosystem assessment: Forest models help estimate carbon storage potential and monitor biodiversity services by showing the true three-dimensional structure of the stand.
• Monitoring and forecasting: By updating the digital twin over time, managers can detect subtle changes before they become visible in traditional inventories, supporting proactive management.
• Risk assessment: Detailed models allow simulation of wind, fire, or pest impacts, helping foresters prepare and reduce risk.

Considerations and Challenges

• Cost and expertise: TLS equipment and data processing require investment and training, making it more accessible to larger operations or research institutions at present.
• Scale limitations: Dense or very large forests may require multiple scans and significant computing resources to create accurate models.
• Actionable data: Generating a digital twin is only valuable if it informs management decisions, including harvesting, restoration, and biodiversity strategies.

Despite these considerations, forest digital twins represent a significant step toward more data-rich, high-resolution management practices. They bridge the gap between traditional forest inventories and emerging ecological modelling, giving managers a clearer picture of the structure and health of their forests. As the technology becomes more widely available and cost-effective, it is likely to play an increasing role in sustainable forestry and ecosystem monitoring.