How AI Wildfire Modeling is Improving Decision-Making

Learn how AI wildfire modeling helps fire agencies predict fire spread, assess risk, and make faster, data-informed decisions during wildfire response and planning.

Current and emerging AI technology has greatly improved our ability to model and predict wildfire risk, behavior, and spread. This provides a significant advantage to fire and emergency personnel who are responsible for making quick, effective decisions in response to active and potential wildfires. This article explores the ways in which AI can currently be used in these areas, as well as emerging research and development in the field of AI wildfire modeling.

What Is Wildfire Modeling and How It’s Used

Wildfire modeling can be used to model both wildfire and prescribed fire behavior. Modeling systems use a variety of data to predict how and when wildfires will happen, and how they will behave.¹ Modeling can be a useful tool utilized by the fire service, insurance companies, utility companies, and emergency planners.²

Using AI to Predict Fire Behavior and Spread

AI can help to predict fire behavior and spread by analyzing and incorporating data more quickly than traditional wildfire models, which allows more data to be used to continually update wildfire forecasts. AI can also quickly recognize potentially inaccurate data, and use prior information in situations where new data is insufficient or non-existent.³

Real-Time Analysis with Weather, Fuel, and Terrain Data

Wildfire modeling systems such as the Behave Fire Modeling System utilize point-based mathematical models to forecast fire environment and fire behavior.¹ They require data about weather, fuel requirements, and topography in order to calculate fire size, intensity, spread rate, and spotting distance.

In a 2024 study, researchers at USC shared a newly developed wildfire forecasting model that utilizes generative AI in combination with satellite data to accurately forecast wildfire spread. Satellite data used to track the progression of a wildfire in real-time was entered into a computer algorithm. The algorithm was able to successfully predict the fire’s most likely path, intensity, and growth rate.⁴ The researchers’ data analysis showed how fire patterns were impacted by factors such as weather, terrain, and fuel.

Creating Fire Path Forecasts to Guide Suppression Strategies

Wildfire spread modeling can assist fire and emergency personnel in forecasting the speed and direction a fire will travel in.² This can help to guide plans for fire suppression, including strategies, placement of equipment, and movement of personnel.

Supporting Smarter Decisions During Wildfire Events

AI wildfire modeling allows for quicker, better-informed decision-making during fire events. In addition to guiding evacuation planning, AI frameworks can also assist in determining appropriate responses from fire and emergency agencies.

Evacuation Planning Based on Predictive Fire Movement

Evacuation planners can utilize wildfire modeling to anticipate where a wildfire will spread and how fast.² These predictions can assist in determining which specific locations and populations will need to be evacuated during a fire.

Researchers at Washington State University are using machine learning models that incorporate how people acted during the 2019 Tick Fire. Including data based on human behavior may help to shape future evacuation policies and planning, such as identifying likely areas of high congestion and bottlenecks.⁵

A team of researchers from multiple universities is also working to develop a wildfire simulation framework informed by psychological theory in order to better predict how people will behave during wildfire evacuation. Such models will be able to assist fire and emergency personnel with decision-making in real-time.⁶

Determining Response Scenarios Before Deployment

Information provided by AI-based wildfire modeling can be essential in determining where and when firefighting efforts and resources should be assigned.⁷ Fire service and emergency agencies can utilize predictions of fire speed and movement in order to determine the most effective ways and areas to approach the fire.

Using AI for Wildfire Mitigation and Land Use Planning

AI systems can be useful tools for mitigating wildfire risk through fuel mapping and land use planning. High risk areas can be identified and addressed ahead of potential wildfire outbreaks, allowing for data-informed decision making.

Mapping Fuel Loads and Risk Areas with AI Tools

AI-based platforms can be utilized to map fuel loads and risk areas that can lead to increased potential for wildfires. UCLA researchers recently developed a system called FuelVision, which incorporates satellite imagery and AI to quickly identify areas of wildfire fuel. In testing, the system had a 77% accuracy rate in mapping fuel loads.⁸

Prioritizing High-Risk Zones for Treatment and Outreach

Information on wildfire fuels is an essential component in being able to predict wildfire behavior and assist in fire risk mitigation planning.⁹ Once a high-risk area is identified, fire service agencies can develop strategies for treatment of fuels, appropriate land use planning, and community outreach in order to mitigate wildfire risk.

What Fire Agencies Should Consider When Using AI Tools

AI has been used in an increasing number of ways to improve and benefit many areas of the fire service. However, it is important to proceed with caution as many AI technologies are quite new and still undergoing refinement.

Prior to introducing AI technology to your agency, make sure to thoroughly research and compare available systems and tools. Evaluate potential risks or negative outcomes, in contrast with the anticipated benefits of using them.

AI frameworks and models, though less likely to produce errors than traditional wildfire models, are not going to be 100% accurate, 100% of the time. Human involvement is still an essential component of wildfire mitigation, planning, and response.

FAQs

• What is the 30-30-30 rule for wildfires?
  • The 30-30-30 rule is a guideline for predicting wildfire risk. If the wind speed is 30km/hour (19mph) or higher, the temperature is higher than 30*C (86*F), and the humidity is 30% or less, there is a heightened risk of fire.¹⁰ 
• What does wildfire modeling mean?
  • Wildfire modeling uses a variety of data to predict how and when wildfires will happen, and how they will behave.¹ Modeling can be useful for anticipating wildfire risk, staging resources, and predicting fire growth.
• What is the spread model of a wildfire?
  • The spread model of a wildfire uses information on wind, humidity, fuel, and other factors to predict the speed and direction of a fire.²