REFERENCE CASE: THE CITY OF HELSINKI IS IMPROVING RISK MONITORING OF STREET AND PARK TREES USING LASER SCANNING AND A SPATIAL DATA MODEL
Laser scanning–based identification of declining trees
In 2025, KOKO Forest delivered a laser scanning and geospatial data–based risk model for the City of Helsinki. The goal was to identify declining street and park trees based on growth and location, to support the prioritization of maintenance. The work utilized laser scanning datasets from two different years, from which growth-related indicators were derived. In addition, tree condition was assessed in the field to support model development and interpretation of the results.
The project continued a pilot study conducted in 2024
A classification model specifically designed for early risk screening was used to identify declining trees. The goal was to detect as many declining trees as possible so that monitoring and closer inspection could be targeted to the right trees. Spatial information was utilized through both regional trends and local environmental features, which improved the model’s ability to identify high-risk areas and individual trees.
As an output, the City of Helsinki received, for each tree, an estimate describing the level of decline risk as well as a high-level prioritization, enabling maintenance actions to be targeted more efficiently. The solution supports operational decision-making by providing an up-to-date and consistent geospatial view of where monitoring and interventions should be focused first.
Deliverables:
✓ Tree-level growth indices based on research
✓ Tree-level maintenance prioritization classifications
✓ A detailed report describing the project and the resulting dataset, including maps