Biome-scale fire severity mapping using moderate-resolution satellite imagery and fire regimes modelling

Background Northern Australia’s tropical savannas, covering 1.8 M km2, are dominated by grassy eucalypt woodlands. Substantial annual rainfall produces abundant fine-fuel biomass while long annual dry periods result in some of the world’s most frequently burned landscapes. Fire severity strongly influences biodiversity and greenhouse gas emissions but remains difficult to map consistently at biome scales. Aims To develop and validate a biome-scale fire severity mapping framework that generates annual fire severity mapping across north Australia, using MODIS 250 m reflectance data, moderate-scale burnt area mapping, active fire data and a large field dataset of fire impacts. Methods We derived the relative difference in the near-infrared (RdNIR) for 10-day median end-of-month image composites, stratified by season, in three distinct pyro-geographical regions, and undertook a supervised classification from extensive field data. Results The calibrated approach achieved 93% overall accuracy. Adjusted thresholds reduced overall overclassification of severe fires in low-canopy environments, markedly improving correspondence with field data. Implications This framework delivers a biome-scale fire severity map for Australia’s tropical savannas, critical for biodiversity conservation, emissions accounting and Indigenous-led savanna burning projects. Limitations include reliance on NIR alone. Incorporation of fractional cover and short-wave infrared (SWIR) data represents a priority for future refinement. Extensive field data are key to accuracy.