Linda Forest provides a step-change in the accuracy of wood mass prediction in standing forests by applying Artificial Intelligence (AI) to satellite, geology and other data.
Forestry firms currently spend up to 30% of their budget on the purchase of wood, without knowing what they are buying. Furthermore, current models are inaccurate by 20%-50% and do not account for climate change or microclimates.
Applying AI to a complex set of terrestrial and satellite data, CollectiveCrunch reduces prevailing error rates by 80%. To do this, Linda Forest uses VHR2 image of Europe from Copernicus Land Monitoring Service, Sentinel-2 images for growth modelling, and Copernicus Climate Change Reanalysis data for microclimate modelling and growth predictions. This means that saw mills and pulp & paper plants will now know the quality and quantity of wood they are buying, resulting in significant efficiency gains.


User Interface Linda Forest, © CollectiveCrunch

 

Customer benefits

Saw mills and pulp & paper plants will now know the quality and quantity of wood they are buying. This brings them efficiency gains of 5-10% in a EUR 8.3 billion market.
Same technical solution can also be offered to insurance firms to value ensured assets and assess risks.

Expertise

“The project offers a convincing solution in terms of technology, business concept and market knowledge. It is clear that the use of Copernicus data and its free accessibility bring a high-added value to the project.” – Michel Massart and Catharina Bamps, Policy Officers, European Commission

Prof Wolfgang Wagner, Christof Danzl, Jarkko Lipponen, Rolf Schmitz

www.collectivecrunch.com