Objectives of the service
Forest owners and managers often rely on manual sample plots and extrapolated inventory data, resulting in incomplete or outdated information about forest conditions. Pollination monitoring faces a similar challenge, where stationary sensors provide detailed measurements but limited spatial coverage.
SPACE-FOREST addresses these challenges through an autonomous and modular ground-based data-collection service. The robot operates beneath the forest canopy and collects geo-referenced sensor data across selected areas. For forest inventory, the service provides measurements such as tree position, diameter at breast height and stand-level information, with additional metrics included as they are validated. For pollination monitoring, specialised sensors are transported between sampling locations to increase spatial coverage without repeated manual relocation.
Tess Space operates and maintains the robotic platform and converts the collected sensor data into customer-ready outputs delivered through reports, spreadsheets, geospatial datasets, APIs or partner platforms.
Users and their needs
The initial target users are forest and agricultural stakeholders in Denmark. Forest inventory is the primary application, while pollination monitoring provides a second application for the same modular robotic platform.
- Forest owners, forest managers, rangers and forestry advisers need representative and up-to-date information on forest conditions while reducing the skilled manual work associated with conventional sample-plot measurements. Data must be geo-referenced, documented and compatible with existing forest-management systems.
- Larger estates and professional forest-management organisations need systematic information that supports planning, harvesting, valuation, certification and traceability.
- Plantation managers, agronomists and pollination-monitoring providers need pollinator observations across multiple locations without repeatedly relocating stationary sensors manually.
- Forest-management software providers and environmental sensing companies need structured data interfaces and a mobile sensing platform that can extend their existing services into under-canopy forestry and plantation monitoring.
Across the user groups, the main requirements are reliable measurements, low-impact field operation, reduced manual effort, integration with existing workflows and transparent service-based pricing.
Service/ system concept
SPACE-FOREST provides an end-to-end service covering mission planning, autonomous field operation, sensing, data processing and delivery of customer-ready results.
The customer first defines the survey area, required measurements and available site information. TESS DRIVE converts these inputs into routes, waypoints or sampling locations. The Tess Space unmanned ground vehicle then executes the mission using their autonomous control system for localisation, navigation, and obstacle avoidance.
For forest inventory, the robot collects LiDAR, camera and positioning data while travelling through the selected stands. For pollination monitoring, the robot carries a specialised Evolito sensor to predefined locations and remains stationary while measurements are taken.
Recorded data are processed using TESS ANALYTICS, including geo-referenced 3D reconstruction, tree detection, trunk fitting and extraction of inventory measurements. Results are packaged as GeoJSON, CSV, reports, point clouds or API outputs and can be integrated into platforms such as Forsler or delivered through partners such as Evolito.
Space Added Value
SPACE-FOREST combines satellite Earth Observation and satellite navigation with detailed ground-based measurements.
Earth Observation provides large-scale information for mission planning, including identification of forest stands, vegetation conditions and areas where detailed inspection is most valuable. This information supports definition of survey boundaries, access routes and robot missions before deployment.
Satellite navigation provides global positioning and geo-referencing of measurements where satellite visibility permits. Beneath dense forest canopy, where GNSS performance can degrade, onboard LiDAR, cameras and inertial sensing maintain local navigation. Global positioning can then be restored when suitable GNSS information becomes available.
The combination is important because satellite and aerial observations provide efficient regional coverage but cannot directly observe many trunk-level and under-canopy characteristics. The robot complements these space-based observations with high-resolution ground measurements. SPACE-FOREST therefore combines satellite-based overview and mission planning with detailed, geo-referenced measurements collected directly on the ground.
Current Status
SPACE-FOREST reached prototype and field-validation stage. The Tess Space UGV completed autonomous predefined routes in representative forest environments while collecting sensor data. Forest data were processed into geo-referenced 3D reconstructions, and tree stems were detected and used for DBH estimation. Validation against manual measurements of 20 trees near Aalborg resulted in a mean absolute DBH error of 4.8 cm, corresponding to approximately 9% mean absolute percentage error.
A specialised Evolito insect sensor was also integrated and tested on the robot. The trials showed that the robot could transport the sensor between sampling locations. Measurements while moving were degraded by platform motion, while stationary measurements were feasible, establishing a practical drive-stop-measure operating concept.
The KickStart work confirmed the technical feasibility of both applications, with further work focused on analytics accuracy, robustness, larger-scale operation and customer integration.
Prime Contractor(s)
