Virtsilv is a platform that uses artificial intelligence (AI) and light detection and ranging (LIDAR) technology to improve sustainable forest management. Developed and tested in Romania, Virtsilv is designed to ensure the sustainability of forestry resources by preventing illegal activities and fraud in the illegal trade of wood products.
To collect data about forests and trees, Virtsilv uses mobile LIDAR systems to gather information about the number, position, and characteristics of trees in an area of interest (AOI). The AOI must be a forested area with a sufficient density of trees to allow the LIDAR system to collect information about individual trees. The LIDAR operator must obtain a full, all-around map by collecting data from different angles and positions around the perimeter of the AOI.
Once the LIDAR data has been collected, Virtsilv processes it through a series of steps to extract data analytics and build mathematical models of individual trees. The process begins with data ingestion and initial settings, followed by the extraction of the ground level model and the separation of trees from soil. The system is then calibrated for optimal tree segmentation through a trial and error process using machine learning techniques. Individual trees are then extracted, and mathematical models are built for each tree based on in situ data and theoretical formulas.
The results of the processing chain are exported to a local database and used to generate data analytics, such as the number of trees, total trunk wood volume, average height, and tree density. These insights and information can be valuable for a range of forestry applications, including resource planning, biodiversity conservation, and climate change mitigation.
By using AI and LIDAR technology to collect and analyze data about forests and trees, Virtsilv is making a valuable contribution to the efforts to improve sustainable forest management and support the long-term health and sustainability of forests. The platform helps reduce the time and resources required to gather data about forests and trees, and provides valuable insights that can inform decision-making and support the responsible use of forestry resources.