A new service that recommends forested areas for thinning
Estonian and Latvian forest software companies have lacked the knowledge and investment to adopt new digital these technologies related to application of the most actual remote sensing data and analytics. This project aims to address these gaps and offer practical solutions for private forest management. In addition, with increasing CO2 market activity, forest owners will soon trade CO2 credits based on their forests' carbon-binding capacity. However, only well-maintained young forests are eligible. This project will develop a service to help forest owners identify areas for cleaning and thinning using remote sensing data and machine learning.
Therefore project aim is to develop a fully automated ML4HealthyForest service for at least 300 private forest owners (with approximately 100,000 ha of forest land) in Estonia and Latvia, which provides objective automated forest management recommendations based on remote sensing data, modeling, machine learning (ML) and automated forest growth algorithms. The results will be easy accessible via ForestMan, ForestRadar web applications or API.
Lead partner:
Baltic Satellite Service LLC (Latvia)
Project partner:
Eeway LLC (Estonia)
