Speakers
Description
Forestry operations require the creation and maintenance of internal networks called extraction trails (cloisonnements), which are essential for machine movement and silvicultural work.
Currently, marking and updating these networks in the field remains costly, time-consuming, and sometimes imprecise.
The SCAN project aims to modernize and optimize the management of these infrastructures by using remote sensing technologies, digital mapping, and machine guidance systems.
The main objectives are to:
• Reduce operational costs,
• Improve the precision of silvicultural operations,
• Limit the impact of interventions on soils,
• Improve working conditions for field teams,
• Ensure better continuity and traceability of data between operations.
The project is based on the systematic digitization of forest plots before machine operations take place.
This approach makes it possible to:
• Identify existing extraction trails or determine optimal routes,
• Prepare operations in advance through data analysis,
• Provide operators with digital materials that can be directly used in the field,
• Reduce manual marking and optimize machine movements.
The generated data are then stored and reused to improve long-term management and monitoring of forestry operations.
To address the diversity of forest conditions (terrain, stands, accessibility), the project aims to :
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Test multiple technologies for integration into the reference data collection process
• High-density LiDAR: produces a detailed 3D representation of the terrain, capable of detecting fine structures and historical traces.
• Very high-density LiDAR (drone): provides detailed 3D terrain acquisition on demand, independent of temporal constraints.
• Drone photogrammetry: generates recent orthophotos, particularly useful in hard-to-access areas.
Additionally, a mobile or terrestrial LiDAR will be used as a reference for high-precision measurements and data validation. -
Test guidance technologies for specialized machinery
• Guidance system (GNSS / RTK / UHF): enables precise vehicle guidance, including in areas without network coverage, using radio base stations.
Initial work shows that LiDAR data can :
• Reveal old or barely visible trails,
• Identify topographic irregularities,
• Generate digital terrain models and analyses (slope, shading, micro-topography).
Using these data in GIS software facilitates :
• The detection and routing of extraction trails,
• The production of operational maps and tools for field use,
• A significant reduction in the time required for field marking.
Machine guidance trials also confirm the potential of these tools, enabling more precise and consistent work, even in varied forest conditions or in areas without network coverage.
By combining remote sensing, geographic information systems, algorithmic processing, and machine guidance, the SCAN project proposes a renewed approach to forestry operations. This methodology aims to improve operational efficiency, reduce costs, preserve soils, and enhance working conditions in the field.
| Keywords | soil; skidtrail; guidance; geospatial |
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