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Projecting live fuel moisture content via deep learning

Year of Publication
2023
Publication Type

Background: Live fuel moisture content (LFMC) is a key environmental indicator used to monitor for high wildfire risk conditions. Many statistical models have been proposed to predict LFMC from remotely sensed data; however, almost all these estimate current LFMC (nowcasting models).

Trends in western USA fire fuels using historical data and modeling

Year of Publication
2022
Publication Type

Background: Recent increases in wildfire activity in the Western USA are commonly attributed to a confuence of factors including climate change, human activity, and the accumulation of fuels due to fire suppression. However, a shortage of long-term forestry measurements makes it difficult to quantify regional changes in fuel loads over the past century.