@article {bnh-5685, title = {Multi-scaled calibration of high-resolution burnt area and fire severity mapping - workshop report}, number = {483}, year = {2019}, month = {07/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Many remote Indigenous communities in the tropical savannas of northern Australia reply upon {\textquotedblleft}Savanna Burning{\textquotedblright} methods, as payment for ecosystem services, providing employment and supporting their livelihoods. The methods rely upon accurate science to calculate greenhouse gas emissions. The current methods use fire seasonality to discriminate emissions estimates, whereas fire severity, if mapped with adequate accuracy, will provide a greenhouse gas emissions method more appropriate to customary burning, by advantaging low severity fires, that has the added advantage of being of overall benefit to biodiversity.
In November 2018, we brought an international group of remote sensing scientists together to develop a collaborative program to increase the spatial resolution of current burnt area mapping programs and incorporate fire severity within them. This report firstly outlines the requirements for the products and summarises the findings of the workshop.

}, keywords = {Fire, Fire danger rating, fire severity mapping, multi-scale, workshop}, issn = {483}, author = {Andrew C. Edwards} } @article {bnh-6321, title = {Geographic Patterns of Fire Severity Following an Extreme Eucalyptus Forest Fire in Southern Australia: 2013 Forcett-Dunalley Fire }, journal = {Fire}, volume = {1}, year = {2018}, month = {10/2018}, abstract = {

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{\textperiodcentered}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.

}, keywords = {aerial photography, Eucalyptus forest, fire intensity, fire severity mapping, generalized linear modelling, geospatial validation, normalized burn ratio, Tasmania}, doi = {https://doi.org/10.3390/fire1030040}, url = {https://www.mdpi.com/2571-6255/1/3/40}, author = {Mercy Ndalila and Grant Williamson and David Bowman} }