Fire severity is an important characteristic of fire regimes; however, global assessments of fire regimes typically focus more on fire frequency and burnt area. Our objective in this case study is to use multiple lines of evidence to understand fire severity and intensity patterns and their environmental correlates in the extreme 2013 Forcett-Dunalley fire in southeast Tasmania, Australia. We use maximum likelihood classification of aerial photography, and fire behavior equations, to report on fire severity and intensity patterns, and compare the performance of multiple thresholds of the normalised burn ratio (dNBR) and normalized difference vegetation index (dNDVI) (from pre- and post-fire Landsat 7 images) against classified aerial photography. We investigate how vegetation, topography, and fire weather, and therefore intensity, influenced fire severity patterns. According to the aerial photographic classification, the fire burnt 25,950 ha of which 5% burnt at low severities, 17% at medium severity, 32% at high severity, 23% at very high severities, while 22% contained unburnt patches. Generalized linear modelling revealed that fire severity was strongly influenced by slope angle, aspect, and interactions between vegetation type and fire weather (FFDI) ranging from moderate (12) to catastrophic (>100). Extreme fire weather, which occurred in 2% of the total fire duration of the fire (16 days), caused the fire to burn nearly half (46%) of the total area of the fireground and resulted in modelled extreme fireline intensities among all vegetation types, including an inferred peak of 68,000 kW·m−1
in dry forest. The best satellite-based severity map was the site-specific dNBR (45% congruence with aerial photography) showing dNBR potential in Eucalyptus
forests, but the reliability of this approach must be assessed using aerial photography, and/or ground assessment.
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