As global warming accelerates, wildfires worldwide are increasing in frequency, intensity, and duration, with extreme forest fires becoming more frequent and severe. Wildfires devastate ecosystems, amplify carbon emissions, thereby form a positive feedback loop with climate change, making them a critical concern in global environmental change research. Wildfire occurrence and behavior are driven by complex interactions among climate variability, meteorological conditions, vegetation characteristics, ignition sources, and human fire management practices. While complete prevention remains infeasible, their impacts on ecosystems and human societies can be mitigated through proactive control measures.
Effective wildfire management hinges on timely and precise monitoring. Independently developed by the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), the Wildfire Satellite Monitoring and Early Warning System is an AI-driven platform leveraging satellite big data, AI-powered remote sensing algorithms, intelligent fire detection, and rapid alert dissemination. This system integrates methodologies, models, data, and software/hardware components, forming an open constellation network utilizing over a dozen satellites to achieve early detection of small fires and continuous tracking of large-scale blazes across East Asia. Additionally, the system provides comprehensive functionalities, including wildfire risk forecasting, fire spread simulation, post-fire impact assessment, and emission quantification. It serves government agencies, research institutions, and sectors including emergency management, forestry, environmental protection, and power grid safety, providing critical data support for real-time tracking of wildfire occurrence and progression, formulating effective firefighting strategies and pollution control measures, and advancing climate change research.
Figure 1: System interface showing active fire detection
Core Features:
Developed to meet the stringent requirements for timeliness and accuracy in wildfire monitoring across diverse application domains,the system has undergone five years of extensive field validation in China's major forest regions. Its performance metrics—including response speed,locational accuracy,false alarm rate,and operational stability—meet international leading standards,ensuring reliability for multi-departmental operational needs. Key functionalities as a daily wildfire monitoring tool include:
1. Real-Time Wildfire Alerts
The platform integrates data from over a dozen polar-orbiting and geostationary satellites,leveraging their complementary advantages through advanced cloud detection,thermal anomaly retrieval,and noise filtering technologies. This enables near-real-time,precise wildfire monitoring across East Asia.
2. Wildfire Risk Forecasting
The system integrates satellite remote sensing,atmospheric modeling,and ground-based big data,accounts for multiple hazard-inducing and risk-enhancing factors,such as meteorological conditions,vegetation phenology and moisture content,topography,and lightning activity,and employs independently developed AI wildfire risk prediction technology to issue proactive early warnings for high-risk zones and provide data-driven support for strategic resource deployment in key fire-prone areas.
3. Post-Fire Damage Assessment
Using multi-source high-resolution satellite data,the system intelligently detects pre- and post-fire landscape changes to assess burn severity and the extent of the affected area.
4. Open Burning Wildfire Emission Accounting
The system employs dynamic emission accounting technology,integrating multi-source geostationary and polar-orbiting satellite data,to quantify pollutants and greenhouse gas emissions from wildfires in near-real-time,providing critical technical and data support for evaluating air quality impacts and formulating emission control strategies.
Product Lead
Contact: Prof. Tao Jinhua
Email: taojh@aircas.ac.cn
Tel: +86 10 6488 9545
