New Technology in Wildfire Forecasting

Explore how AI, satellite data, and real-time tools are transforming wildfire forecasting and helping agencies predict fire spread faster and more accurately.

As wildfires continue to increase in severity, research and technology have increased our ability to accurately forecast their incidence, intensity, and spread. This article explores new technologies and abilities in the field of wildfire forecasting, as well as the role that Artificial Intelligence can play in new forecasting models. The development of new forecasting technology is a valuable tool in the continuing fight against wildfires.

Why Accurate Wildfire Forecasting Matters More Than Ever

Across the country, wildfires cost billions of dollars annually, in addition to causing numerous injuries and fatalities. With wildfire severity expected to increase in coming years, the ability to accurately and efficiently predict where and how they will spread is essential now more than ever.¹ Wildfire forecasting has the ability to help save lives and property, improve the safety of firefighters, and enhance wildfire response.

Breakthrough Technologies Transforming Wildfire Forecasting

New technologies are continually being developed in efforts to improve abilities to forecast wildfires. Recent advancements have been seen in the fields of artificial Intelligence, weather modeling, satellites, drones, and modeling systems.

AI and Machine Learning for Fire Spread Prediction

AI and machine learning can help to enhance wildfire forecasting by addressing common limitations that impact traditional wildfire models. AI models assimilate data more quickly, which allows more data to be used to continually update wildfire forecasts. AI can also recognize potentially inaccurate data more quickly, and use previous information for modeling in situations where new data is not sufficient or does not exist.¹

In a study published in 2024, 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 likely intensity, path, and growth rate of the fire.² The researchers’ data analysis showed how fire patterns were impacted by factors such as weather, terrain, and fuel.

High-Resolution Weather Modeling Systems

Weather prediction models are an essential part of wildfire forecasting. These models can include data on temperature, wind speed, humidity, and precipitation. All of these factors can impact wildfire behavior. Accurate weather modeling can improve our ability to forecast the timing and location of potential wildfires.³

Satellite-Based Technology

Satellites provide data on things like weather, topography/terrain, and vegetation, as well as fire detection and monitoring. This data can be integrated into wildfire forecasting models. New satellites contain sophisticated sensor technology that can survey large areas of land while sensing changes in temperature, moisture, and vegetation which can signal the beginning of a wildfire.^3,4

Drone Data Integration

Drones are utilized at fire scenes to determine location and possibility of spreading. Drones can use thermal cameras to see through trees and smoke, which can provide better information on fire location and intensity. Data from drones can offer enhanced wildfire forecasting when integrated into larger platforms.¹

Fire Modeling Systems

Fire modeling systems can be used for both wildfire and prescribed fire behavior modeling. One example is the Behave Fire Modeling System, which was created in 1984. This system utilizes point-based mathematical models to forecast fire environment and fire behavior.⁵ It requires data about weather, fuel requirements, and topography in order to calculate fire size, intensity, spread rate, and spotting distance. An updated version, Behave⁷, was recently introduced with design improvements.⁶

How Fire Agencies Are Using Forecasting Tools in the Field

Wildfire forecasting tools are used nationally and locally to provide predictions on fire danger, occurrence, behavior, fuels, and assets needed. Across agencies, forecasting is utilized by incident managers, fire management personnel, firefighters, and other support staff. Current forecasting tools can provide information to these personnel on wildfire preparedness levels, mapping, satellite imagery, firefighting assets, fire situations, fire potential, risk level, climate, weather, and smoke.⁷

Challenges and the Future of Wildfire Forecasting Tech

As wildfire forecasting technology continues to be developed and improved, researchers are challenged with the task of determining which types of data will be the most impactful for predicting future fires, the best way to gather this data, and the most effective way to utilize the data. AI is now playing a larger role in wildfire forecasting, and like any new technology it must be implemented with caution and appropriate oversight. The field of wildfire forecasting technology is an exciting area of research and development that will have significant impacts on our ability to accurately predict and fight wildfires in the future.

FAQs

• What is fire forecasting?
  • Fire forecasting is the process of analyzing data across weather, climate, fuels, and fire activity, and using it to predict potential fire size, intensity, and spread.^6,7
• Can AI predict wildfires?
  • Artificial Intelligence can be used to predict the spread of wildfires.²
• Are AI models reliable for predicting wildfires?
  • Wildfire forecasting models using AI have been shown to reliably predict wildfires.²
• Can communities use wildfire forecasting tools?
  • Communities can benefit from using wildfire forecasting tools to predict the risk, intensity, and spread of wildfires in local areas.