A Comprehensive Remote Sensing–Driven Inventory Across Millions of Hectares

Challenge

Finland’s forest landscape is immense, diverse, and continuously evolving. Traditional field-based data collection cannot keep pace with the growing need for up-to-date, nationwide forest information.

Rather than a problem, this is a natural capacity challenge faced by many countries with large forest estates.

Solution

To support effective, fair, and timely decision-making, Finnish Forest Centre needed a method that would be fast, consistent, and cost-efficient.

Since 2010, Arbonaut has supported the Finnish Forest Centre with accurate, scalable forest inventory data across more than 8 million hectares.

Arbonaut combined several data sources, each contributing unique dimension to the estimation models for both tree-species attributes and stand-level indicators:

  • LiDAR – primary input for forest structure (height, volume, diameter, basal area)
  • CIR (Color Infrared) imagery – enhances vegetation classification and species differentiation
  • Selective satellite imagery – used when conditions and availability supported additional detail

LiDAR-based data collection and modelling cost €3-€5/ha in Finland, compared to €20/ha for traditional methods, saving the Finnish Forest Centre an estimated €30 million over the years.

To ensure consistency across Finland’s forests, Arbonaut used automatic stand segmentation, producing objective boundaries before applying the inventory models.

Automatic forest stand segmentation fully replaced manual processes and boosted efficiency.

Outcomes

The project demonstrates how coordinated remote sensing, field data, and modelling can deliver reliable, high-resolution forest inventory information at a national scale. This approach unlocked the creation of value-added products beyond forest inventories such as timber valuation and biodiversity mapping.