From vegetation dynamics to fire risk: a predictive framework

Accurate fire risk estimation requires accounting for fuel moisture and fuel load assessment. Satellite-retrieved vegetation parameters offer valuable insights into fuel characteristics but are challenging to integrate due to the complex and varying interactions between vegetation and bushfires during the pre- and post-fire stages. This study explores the potential of vegetation parameters to predict fire risk independently of fire weather data. Our focus is on the pre-fire stage where the fire risk rises from a minimum threshold, which is a key determinant in bushfire ignition. Using the McArthur Forest Fire Danger Index (FFDI) as a fire danger measure, we found that incorporating vegetation optical depth (VOD) into predictive models significantly enhances the performance compared to models that base past fire risk information alone. VOD was identified as a causal driver of FFDI in a significant number of fire-prone pixels in Australia, and the VOD-induced model outperformed the model that used only the past fire risk information over a 12-month lead span. These findings highlight the potential of vegetation dynamics as a standalone predictor of fire risk when the knowledge on fire weather is uncertain or unavailable. Future research will focus on enhancing this predictive framework by incorporating terrestrial water storage as an additional predictor, building on the recent studies that highlight the effectiveness of terrestrial water storage in explaining the vegetation dynamics variability and reflecting the moisture conditions during pre-fire periods.