Russia Deploys AI to Match Satellite Images with Ground Data
Russia is testing AI‑driven systems that compare satellite data with ground photography to detect forest‑management errors and predict wildfire risks
AI Pinpoints Red Zones
Russia’s Federal Forestry Agency is expanding its use of advanced technologies to improve oversight and accuracy in forest inventory. Agency head Ivan Sovetnikov highlighted the growing role of artificial intelligence paired with satellite imaging in forest assessment and monitoring.
As part of an ongoing experiment, a neural network compares photos taken by field surveyors with satellite images. The system flags mismatches in red—so‑called “red zones”—indicating areas that require on‑site reinspection. The goal is to reduce errors, enhance transparency, and create a more accurate, data‑driven system.
AI is also used in Russia’s timber‑tracking system. Every day, algorithms analyze 22,000 transport routes and monitor the movement of nearly one million cubic meters of wood materials.
Detecting and Preventing Forest Fires
Satellite imaging covers Russia three times a day, automatically detecting thermal hotspots and wildfires even in remote regions. All data is publicly accessible, allowing any resident to view active fires across the country.
Sovetnikov noted that AI could soon predict the likelihood and development of wildfires—not just detect them. Russian engineers have already built prototype systems for fire forecasting, and if ongoing tests prove successful, the technology may be scaled nationwide.
Looking Ahead
The integration of AI, satellite imaging, and digital forestry tools marks a shift toward proactive environmental management. Instead of reacting to damage, the new systems aim to prevent it, providing authorities with faster insights and enabling data‑driven resource allocation.
If fully deployed, these capabilities could significantly improve forest conservation, cut economic losses, and increase public transparency.
