¶ project about laser scanning, aerial photography to create a digital forest twin
| Authors | n.n. |
| Country | Ministry of Agriculture and Forestry of Finland; Finish Forest Centre |
| Paper (PDF) | View paper |
| Category | Planning & Inventory › Remote sensing & mapping |
project still running
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¶ Overview
Digital forest twin projects use a combination of airborne laser scanning (ALS), aerial photogrammetry, and terrestrial or mobile LiDAR to create high-fidelity three-dimensional digital replicas of forest stands or entire estate areas. These digital twins capture the structural characteristics of the forest — including individual tree positions, crown dimensions, stem diameters, heights, and canopy architecture — at a level of detail sufficient to support detailed planning, simulation, and operational decision-making without requiring extensive ground-based measurement. Aerial photography processed through structure-from-motion (SfM) photogrammetry generates dense point clouds and orthomosaic imagery, while LiDAR adds precise elevation and vegetation structure information that penetrates the canopy. Together, these data sources are fused to produce a georeferenced digital model that can be queried, updated, and integrated with forest management information systems. Digital twin applications in forestry include optimising harvesting sequences, planning road and snig track layouts, estimating timber volumes and assortment yields, assessing windthrow risk, and monitoring stand growth between successive surveys. In the Scandinavian context — where much of the foundational research has been conducted — programs such as the Swedish Mistra Digital Forest initiative have explored digital twin frameworks for operational planning and silvicultural decision support. In Australia, organisations including CSIRO, Interpine, and various state forest agencies have undertaken projects combining drone-based photogrammetry and ALS data to create high-resolution forest models for plantation estates, supporting improved inventory accuracy and reducing the cost of manual ground measurement. The maturation of cloud computing, automated point cloud processing, and AI-driven individual tree segmentation algorithms is steadily making digital forest twins more accessible and operationally practical.
¶ Assessment
A high-value strategic tool that strengthens management efficiency and improves risk insight across climate, disturbance, and long-term forest conditions.
¶ Details
| Field | Value |
|---|---|
| Company | n.n. |
| Country | Ministry of Agriculture and Forestry of Finland; Finish Forest Centre |
| Type | Paper |
| Year | 2023-2025 |
| FWPA RD&E | 7.3 |
| Remarks | 0.0 |
| Case Studies | 0 |