FireCon: Daily Fire Containment Suitability

Fire behavior is more extreme and unpredictable than we’ve seen in the past. Changes in climate, wildfire complexity, and forest and fuel conditions outpace even the most advanced fire modeling systems. To navigate this complexity, wildfire responders rely on decision-support tools to reduce risk.

FireCon, or Daily Fire Containment Suitability, is a decision support system for wildfire responders to determine where they’ll have the best chance of successfully containing a fire given current and predicted weather and fuel conditions. Co-developed with Microsoft R&D, the system uses a neural network to incorporate daily variability in fire weather and fuel dynamics, enabling IMTs to adapt fire management tactics and strategies to changing environmental conditions.

A pilot group of researchers and managers are assessing the utility of FireCon during the 2026 fire season, and a public viewer developed for the current and two-day forecast should be coming online soon.
 

FireCon builds on the Potential Control Location (PCL) Suitability map, which uses machine learning to harvest data from over twenty years of past fire containment successes and failures. Whereas the Potential Control Location Suitability map, hosted on the RMA dashboard here, is updated annually and provides a static snapshot of potential control locations, FireCon reflects real-time and forecast conditions. This new model opens the door to more tactical decision-making with greater accuracy and precision. Compared to Potential Control Location Suitability, FireCon more accurately portrays the dynamic fire management environment across the full range of moderate to extreme fire behavior.

FireCon is on track to drastically enhance the wildland fire decision-making environment. A study of the accuracy of Potential Control Location suitability for the 2021-2024 fire seasons found correct classification of control features ranged from 60-85% depending on the severity of fire burning conditions.  FireCon is designed to address the low end of PCL classification accuracy by accounting for more extreme weather and fuel conditions.  Initial results suggest an increased classification accuracy of at least 10% across low, moderate, and high containment suitability classes. 

FireCon was developed through a public-private partnership between the Forest Service Research and Development and Microsoft Corporation. A new data viewer dashboard is in development through a partnership between the Forest Service and Wherobots LLC.

Purpose

FireCon is a decision support system for wildfire responders to determine where they’ll have the best chance of successfully containing a fire. With more accurate data reflecting near real-time and forecast changes in conditions, FireCon has potential to help fire managers to improve success rates of wildfire containment and reduces firefighter exposure to wildfire hazards.

Overview and Applicability

While FireCon reduces decision-making time pressures, it cannot replace human judgment or a fire manager’s experience, nor does it promise success. It also does not account for other important considerations like public safety or fire responder safety.