SingleTree – for an optimal forestry

The SingleTree project runs for four years and is funded by EU funds. The work is coordinated by NIBIO, the Norwegian Institute of Bioeconomy Research, and is supported by 14 partners from Norway, Sweden, Finland, Spain and Switzerland.

SCA represents Scandinavian forestry.  Universities and research institutes, along with companies at the forefront of digital technology is also involved. Everyone sees great opportunities in combining high-resolution data about the forest with AI to develop forestry.

SingleTree will investigate how forest value chains can be optimized using detailed information about individual trees – information obtained by applying advanced digital technology, including AI and remote sensing. The idea is to manage individual trees with precision forestry to ensure the biomass is used optimally for the right products while improving forestry's ability to adapt to climate change and increase forest resilience.

The SingleTree project is divided into five work packages. The first package deals with remote sensing and obtaining data about individual trees. The second package focuses on adaptive forest management, and the third package works with intelligent machines to make use of each tree's information, while work package four will address wood quality to optimize value creation from the forest.

The research and technical solutions developed in these four work packages will then be applied in the fifth work package, called LLVC, Living Lab Value Chain. SCA are involved as Living Lab North. In addition, there are LLVC Central and LLVC South.

LLVC Central is represented by the public forest administration in the canton of Bern in central Switzerland. LLVC South is represented by the Spanish foundation "Foundation Cesefor" in Castilla y León in northwestern Spain, which aims to promote forestry and forest-based industries.

There are quite different forests and different types of forestry participating. SCA is by far the largest forest owner with our 2.1 million hectares of productive forest land, while the canton of Bern manages a total of 13,000 hectares of forest land. 

SCA's role will be to test and apply various solutions in actual operations in our forestry, ensuring that the research has a clear real-world grounding. SCA is also sharing forest data on individual trees, collected bu SCA's own yearly scanning of chosen forests.

SCA is at the forefront when it comes to collecting information about individual trees. This effort has resulted in the internally developed tool SCAn. This work and the tool SCAn are fundamentally changing how SCA plan its harvesting operations.

By utilizing information from the laser scanning of selected forests and data fromSCA's  forestry machines, combined with AI, to create a digital twin of the forest. Thanks to the SCAn, SCA's planners can now perform a large part of the harvest planning at the office. This saves significant time, allows them to plan more efficiently during winter, and enables us to focus on visiting only the areas that truly need field inspections.

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