Implementation of quantitative bushfire risk analysis in a GIS environment
Dale Atkinson A , Mark Chladil B , Volker Janssen A C and Arko Lucieer AA School of Geography and Environmental Studies, University of Tasmania, Private Bag 76, Hobart, TAS 7001, Australia.
B Tasmania Fire Service, GPO Box 1526, Hobart, TAS 7000, Australia.
C Corresponding author. Email: volker.janssen@utas.edu.au
International Journal of Wildland Fire 19(5) 649-658 https://doi.org/10.1071/WF08185
Submitted: 1 November 2008 Accepted: 17 November 2009 Published: 9 August 2010
Abstract
Bushfires pose a significant threat to lives and property. Fire management authorities aim to minimise this threat by employing risk-management procedures. This paper proposes a process of implementing, in a Geographic Information System environment, contemporary integrated approaches to bushfire risk analysis that incorporate the dynamic effects of bushfires. The system is illustrated with a case study combining ignition, fire behaviour and fire propagation models with climate, fuel, terrain, historical ignition and asset data from Hobart, Tasmania, and its surroundings. Many of the implementation issues involved with dynamic risk modelling are resolved, such as increasing processing efficiency and quantifying probabilities using historical data. A raster-based, risk-specific bushfire simulation system is created, using a new, efficient approach to model fire spread and a spatiotemporal algorithm to estimate spread probabilities. We define a method for modelling ignition probabilities using representative conditions in order to manage large fire weather datasets. Validation of the case study shows that the system can be used efficiently to produce a realistic output in order to assess the risk posed by bushfire. The model has the potential to be used as a reliable near-real-time tool for assisting fire management decision making.
Additional keywords: bushfire simulation, fire behaviour, fire probabilities, modelling, Tasmania, wildfire threat analysis.
Acknowledgements
We thank the Tasmania Fire Service, the Bureau of Meteorology (Tasmania Antarctica Region), the Department of Primary Industries and Water and the University of Tasmania for their contribution in providing datasets.
Bachmann A , Allgower B (2002) Uncertainty propagation in wildland fire behaviour modelling. International Journal of Geographical Information Science 16, 115–127.
| Crossref | GoogleScholarGoogle Scholar |
Berjak SG , Hearne JW (2002) An improved cellular automaton model for simulating fire in a spatially heterogeneous savanna system. Ecological Modelling 148, 133–151.
| Crossref | GoogleScholarGoogle Scholar |
Birk EM , Simpson RW (1980) Steady state and the continuous input model of litter accumulation and decomposition in Australian eucalypt forests. Ecology 61, 481–485.
| Crossref | GoogleScholarGoogle Scholar |
Bradstock RA , Gill AM (2001) Living with fire and biodiversity at the urban edge: in search of a sustainable solution to the human protection problem in southern Australia. Journal of Mediterranean Ecology 2, 179–195.
Brandis K , Jacobson C (2003) Estimation of vegetative fuel loads using Landsat TM imagery in New South Wales, Australia. International Journal of Wildland Fire 12, 185–194.
| Crossref | GoogleScholarGoogle Scholar |
Fensham RJ (1992) The management implications of fine fuel dynamics in bushlands surrounding Hobart, Tasmania. Journal of Environmental Management 36, 301–320.
| Crossref | GoogleScholarGoogle Scholar |
Finney MA (2002) Fire growth using minimum travel time methods. Canadian Journal of Forest Research 32, 1420–1424.
| Crossref | GoogleScholarGoogle Scholar |
Genton MG, Butry DT, Gumpertz ML , Prestemon JP (2006) Spatiotemporal analysis of wildfire ignitions in the St Johns River Water Management District, Florida. International Journal of Wildland Fire 15, 87–97.
| Crossref | GoogleScholarGoogle Scholar |
Jones SD, Garvey MF , Hunter GJ (2004) Where’s the fire? Quantifying uncertainty in a wildfire threat model. International Journal of Wildland Fire 13, 17–25.
| Crossref | GoogleScholarGoogle Scholar |
Knight I , Coleman J (1993) A fire perimeter expansion algorithm based on Huygen’s wavelet propagation. International Journal of Wildland Fire 3, 73–84.
| Crossref | GoogleScholarGoogle Scholar |
Marsden-Smedley JB , Catchpole WR (1995) Fire behaviour modelling in Tasmanian buttongrass moorlands I. Fuel characteristics. International Journal of Wildland Fire 5, 203–214.
| Crossref | GoogleScholarGoogle Scholar |
McRae RHD (1992) Prediction of areas prone to lightning ignition. International Journal of Wildland Fire 2, 123–130.
| Crossref | GoogleScholarGoogle Scholar |
Noble IR, Bary GAV , Gill AM (1980) McArthur’s fire-danger meters expressed as equations. Australian Journal of Ecology 5, 201–203.
| Crossref | GoogleScholarGoogle Scholar |
Nunez M , Colhoun EA (1986) A note on air temperature lapse rates on Mount Wellington, Tasmania. Papers and Proceedings of the Royal Society of Tasmania 120, 11–15.
Olson JS (1963) Energy storage and the balance of producers and decomposers in ecological systems. Ecology 44, 322–331.
| Crossref | GoogleScholarGoogle Scholar |
Preisler HK, Brillinger DR, Burgan RE , Benoit JW (2004) Probability-based models for estimation of wildfire risk. International Journal of Wildland Fire 13, 133–142.
| Crossref | GoogleScholarGoogle Scholar |
Raison RJ, Woods PV , Khanna PK (1986) Decomposition and accumulation of litter after fire in subalpine eucalypt forests. Australian Journal of Ecology 11, 9–19.
| Crossref | GoogleScholarGoogle Scholar |
Ripley BD (1976) The second-order analysis of stationary point processes. Journal of Applied Probability 13, 255–266.
| Crossref | GoogleScholarGoogle Scholar |


