Research Database
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Fire Intensity and spRead forecAst (FIRA): A Machine Learning Based Fire Spread Prediction Model for Air Quality Forecasting Application
Year: 2025
Fire activities introduce hazardous impacts on the environment and public health by emitting various chemical species into the atmosphere. Most operational air quality forecast (AQF) models estimate smoke emissions based on the latest available satellite fire products, which may not represent real-time fire behaviors without considering fire spread. Hence, a novel machine learning (ML) based fire spread forecast model, the Fire Intensity and spRead forecAst (FIRA), is developed for AQF model applications. FIRA aims to improve the performance of AQF models by providing realistic, dynamic fire…
Publication Type: Journal Article
Combining ecophysiology and combustion traits to predict conifer live fuel moisture content: a pyro-ecophysiological approach
Year: 2025
Background Fuel moisture content is a key driver of fuel flammability and subsequent fire activity and behavior worldwide. Dead fuels passively exchange moisture with the atmosphere while live fuel moisture is confounded by a mixture of seasonal carbon and water cycle dynamics. Despite the significance of live fuel moisture content (LFMC) on wildland fire potential, attempts to model its variations seasonally and between species are often inconclusive or unsuccessful.ResultsHere we present a mechanistic LFMC model that uses easily measured live fuel…
Publication Type: Journal Article