Potential Control Location Suitability Model

Fire behavior has grown more extreme and unpredictable. 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. Among them, the Potential Control Locations (PCL) Suitability map has become one of the most requested and utilized wildfire decision-support analytics by Complex Incident (Type 1 and 2) Command Teams.
The Potential Control Locations Suitability model uses machine learning and over 20 years of past fire containment successes and failures to identify the best and worst locations for fire containment. The map output is updated annually for the western United States.
Prior to a fire, land managers can use the Potential Control Locations Suitability model to help inform Potential Operational Delineation (POD) boundary locations. During a prescribed or wildland fire, the Potential Control Locations model helps managers rapidly assess containment options, consider the quality of fire control lines, and determine the resources they need to meet management objectives. Further, managers can use the Potential Control Locations Suitability map as a tool to communicate options, strategy, and decisions with partners and stakeholders. Potential Control Locations also serve as the starting condition to the FireCon daily fire containment model.
During the 2022 and 2023 fire seasons, the Potential Control Locations model correctly predicted more than 80 percent of containment successes and 90% of containment failures in the western U.S.

Managers use the PCL Suitability model while preparing for future wildfires at a Potential Operational Delineation (POD) workshop on the Beaverhead-Deerlodge National Forest.
Purpose
The Potential Control Location Suitability model predicts the best and worst locations for engaging fire. It can help fire managers improve their chances of successful wildfire containment and reduce risk of harm to wildland firefighters.
