This technology is a dashboard that has the capability of gathering data from multiple independent forest service data sources to aid in the identification and prediction of potential fire weather, as well as the impact of weather on fire events. Moreover, the dashboard incorporates advanced machine learning algorithms for dynamic and predictive modeling, integrating streamlined data science methods, optimized aggregation, and visualization techniques, along with new fire weather forecast products. These features enable it to adapt to continually changing forest conditions and to provide proactive solutions for potential wildfire threats. Background: Wildfire management presents complex challenges as a result of climate change and shifting weather patterns, which impact fuel and ignition sources. The proposed fire information portal aims to address them by leveraging abundant data for better fire risk management, decision support, and planning. By blending the use of modern data science techniques with more traditional knowledge of fire ecology and meteorology, this technology seeks to bridge the gap between science, decision-making, and on-the-ground firefighting efforts, thereby improving the ability to anticipate and mitigate the risks posed by wildfires. Applications:
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