Ignition Type and Fuel Controls on Wildfire Escape in British Columbia's Coast and Prince George Fire Centres

Understanding the factors that influence wildfire escape is critical for improving fire management and resource allocation. This study aimed to identify environmental drivers of wildfire escape in the Coast and Prince George Fire Centres using a machine learning approach.

Wildfire ignition data were combined with environmental variables describing vegetation, terrain, snow conditions, and fire weather, and Random Forest models were developed to classify whether fires exceeded a 4 ha escape threshold. Model performance showed moderate predictive ability, with approximately 48–49% of escaped fires correctly identified. Results indicate that vegetation characteristics were the strongest predictors of wildfire escape.