According to TASS, the system is based on a neural network that recognizes air photographs with UAVs.
Arseniy Afanasenko, President of the Geoscan Development Department, said Bor allows us to gain comparable accuracy with the traditional re -registration of forests. The system automates processes, except for field research needs and manual data processing in remote areas. According to the expert, the system will become an effective tool for forestry and development of new regions.
Nervous networks automatically divide the forest areas, detect and determine the limits of wood. “Boron” classifies trees according to the species and calculates taxation parameters for each site.
The system analyzes air photos, creates vector cards with the location of the trees, and provides reports about the composition and volume of wood. If the site has previously unidentified rocks, the system automatically classifies them using machine learning methods. Trees with similar properties are combined to layers and determine the operator species.
“Working with the bass of neural networks provides comparable accuracy as a result of a continuous transition and quality meets the requirements of forest management instructions. In this case, it is not necessary to waste time to frequently unreachable areas and manual data processing.
Source: Ferra
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