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Filters: Keyword is Fire behaviour  [Clear All Filters]
2023
Innocent, J., Sutherland, D., Khan, N. & Moinuddin, K. Physics-based simulations of grassfire propagation on sloped terrain at field scale: motivations, model reliability, rate of spread and fire intensity. International Journal of Wildland Fire (2023). doi:https://doi.org/10.1071/WF21124
2021
Begg, C., Dwyer, G., Neale, T. & Pollock, I. Established and emerging uses of predictive services in Victoria. (Bushfire and Natural Hazards CRC, 2021).
Gould, J. S. & Sullivan, A. Initial growth of fires in eucalypt litter, from ignition to steady-state rate of spread: laboratory studies. International Journal of Wildland Fire (2021). doi:https://doi.org/10.1071/WF21094
Filkov, A. Predicting merging fire behaviour in Planned Burning. AFAC21 (AFAC, 2021). at <https://www.afac.com.au/events/proceedings/05-10-21/article/predicting-merging-fire-behaviour-in-planned-burning>
2020
Adams, M. A., Shadmanroodposhti, M. & Neumann, M. Causes and consequences of Eastern Australia’s 2019–20 season of mega‐fires: A broader perspective. Global Change Biology 26, pp. 3756-3758 (2020).
Storey, M., Price, O., Sharples, J. J. & Bradstock, R. Drivers of long-distance spotting during wildfires in south-eastern Australia. International Journal of Wildland Fire (2020). doi:https://doi.org/10.1071/WF19124
Cawson, J. et al. Exploring the key drivers of forest flammability in wet eucalypt forests using expert-derived conceptual models. Landscape Ecology 35, 1775–1798 (2020).
Burton, J., Cawson, J., Filkov, A. & Penman, T. Leaf traits predict global patterns in the structure and flammability of forest litter beds. Journal of Ecology (2020). doi:https://doi.org/10.1111/1365-2745.13561
2019
Peace, M., Kepert, J. & Ye, H. ACCESS-Fire: coupled fire-atmosphere modelling. Bushfire and Natural Hazards CRC Research Day AFAC19 (2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
McRae, R. Experiences with the global impacts of climate change. AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum (Australian Institute for Disaster Resilience, 2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
Fox-Hughes, P. et al. Fire weather and prototype fire danger ratings for the Gell River fire, Tasmania. Bushfire and Natural Hazards CRC Research Day AFAC19 (2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
Reinke, K., Wallace, L., Hillman, S., Hally, B. & Jones, S. Fuels3D: barking up the wrong tree and beyond. AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum (Australian Institute for Disaster Resilience, 2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
2018
Raposo, J. R. et al. Analysis of the physical processes associated with junction fires at laboratory and field scales. International Journal of Wildland Fire 27, (2018).
Filkov, A., Duff, T. & Penman, T. Improving Fire Behaviour Data Obtained from Wildfires. Forests 9, (2018).
2017
Dharssi, I. & Kumar, V. JASMIN: A prototype high resolution soil moisture analysis system for Australia. (Bureau of Meterology, 2017). at <http://www.bom.gov.au/research/publications/researchreports/BRR-026.pdf>
2013
Cruz, M. G. & Alexander, M. E. Uncertainty associated with model predictions of surface and crown fire rates of spread. Environmental Modelling & Software 47, 16-28 (2013).
2010
Pérez, Y., Pastor, E., Planas, E., Plucinski, M. P. & Gould, J. S. Computing forest fires aerial suppression effectiveness by IR monitoring. Fire Safety Journal (2010). doi:10.1016/j.firesaf.2010.06.004