Time-Driven Fire Risk Forecasting: Leveraging Historical Trends for Enhanced Seasonal Modeling

As wildfires sweep across North America each year, leaving a trail of destruction and impacting lives, ecosystems, and properties, our team of data scientists sought to find a formidable solution to this challenging problem. This study delves into the core of accurate fire prediction and forecast outlooks, harnessing the power of historical fire risk data to empower effective mitigation strategies. 

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With agencies like the NIFC and CWFIS as our cornerstones, we delve into weather-based fire risk models, dissecting the impact of time on accuracy. Our study uses two encoding techniques – One-Shot and Year-By-Year – highlighting their divergent attributes in fire risk assessment.

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The research finds that while the One-Shot model exhibits exceptional accuracy, the Year-By-Year model offers alternative insights, both adept at utilizing historical fire weather data for forecasts. This research guides future model design, fortifying wildfire management strategies and safeguarding landscapes.

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Download the research paper to delve into the depths of our research and gain access to invaluable insights that could reshape the way we manage fire risks in the future.

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