Collecting Accurate Individual Tree Information for Harvester Operation Decision Making

Description of the granted funding

If we remove too much wood from the forests in the first thinnings, it lowers the growth of forests and carbon intake jeopardising greenhouse gas emission reduction targets. 2022 PONSSE launched a technology concept introducing a thinning density assistant based on mobile laser scanning (MLS). The thinning density assistant technology concept works by detecting the trees around the harvester and suggesting a target number of trees to be left in the forest in order to reach an optimal thinning volume. However, the decision made by the harvester operator would be more accurate, if more knowledge of the standing trees were available. Thus, the core idea of the proposed project is to improve technologies related to the world-first thinning density assistant in order to be able to meet the requirement of various forest ecosystem services by two key technologies: by creating a detailed digital replica of forests before harvesting and by improved processing of the harvester MLS.
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Starting year

2024

End year

2025

Granted funding

Juha Hyyppä
300 000 €

Funder

Research Council of Finland

Funding instrument

Targeted Academy projects

Decision maker

Scientific Council for Natural Sciences and Engineering
13.12.2023

Other information

Funding decision number

359554

Fields of science

Environmental engineering

Research fields

Kaukokartoitus

Identified topics

forest, forestry