Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Assessing the capabilities of geospatial data to map built structures and evaluate their bushfire threat

Kim Lowell A B F , Ron Shamir C , Andreia Siqueira D , John White D , Alice O’Connor E , Gary Butcher E , Mark Garvey C and Michael Niven D
+ Author Affiliations
- Author Affiliations

A Cooperative Research Centre for Spatial Information, Ground Floor, 723 Swanston Street, Carlton, VIC 3052, Australia.

B Present address: Department of Primary Industries, 32 Lincoln Square North, Carlton, VIC 3052, Australia.

C Country Fire Authority Victoria, 8 Lakeside Drive, Burwood East, VIC 3151, Australia.

D Victorian Department of Sustainability and the Environment, 8 Nicholson Street, East Melbourne, VIC 3052, Australia.

E Geomatic Technologies, Level 6, 4 Riverside Quay, Southbank, VIC 3006, Australia.

F Corresponding author. Email: klowell@crcsi.com.au

International Journal of Wildland Fire 18(8) 1010-1020 https://doi.org/10.1071/WF08077
Submitted: 19 May 2008  Accepted: 5 May 2009   Published: 9 December 2009

Abstract

Bushfire threat was evaluated for built structures for three areas in Victoria (Australia) that had been impacted by the devastating 16 February 1983 Ash Wednesday fires. Structures were mapped for 1982 and 2006 using human interpretation of high-resolution (0.35-m pixels) digital orthophotographs. Damage to structures from the 1983 Ash Wednesday fires was also evaluated using human interpretation of the digital orthophotographs. Approximately 25% of the structures present were not mapped due to either interpreter error or overhanging vegetation. The majority of unmapped structures were sheds and garages. The error of omission for houses was between 7 and 10% with the error of commission for houses being less than 0.5%. Bushfire threat was modelled using information about topographic slope and aspect, forest vegetation, and prevailing wind direction during days of high fire danger. The method detected a substantial change in bushfire threat from 1982 to 2006 for one of the three study sites whereas no change in overall bushfire threat was observed for the other two. Considering the location of structures built since 1982, these results appeared reasonable. However, the 1982 bushfire threat was not related to actual structure damage sustained during the 1983 Ash Wednesday fires. Estimating bushfire threat using this methodology cost AU$6 per structure or AU$4.60 per property.


Acknowledgements

The authors thank Liam Fogarty of the Department of Sustainability and Environment for financing this work, and the Department of Sustainability and Environment and Country Fire Authority for contributing a significant amount of human resources to this project. The lead author would like to specifically acknowledge the contributions of coauthors G. Butcher and A. O’Connor for overseeing all aspects of structure mapping, R. Shamir for analysis of weather data and the development of the bushfire threat model, A. Siqueria for undertaking the majority of the vegetative mapping, and J. White for general data provision and all processing associated with the TreeDen algorithm.


References


Alexander J, Seavy N, Ralph J , Hogoboom B (2006) Vegetation and topographical correlates of fire severity from two fires in the Klamath-Siskiyou region of Oregon and California. International Journal of Wildland Fire  15, 237–245.
Crossref | GoogleScholarGoogle Scholar | Andrews P, Bevins C (1998) Update and expansion of the BEHAVE fire behaviour prediction systems. In ‘Proceedings of the 14th Conference on Forest Fire Research and 14th Conference on Fire and Forest Meteorology’, 16–20 November 1998, Luso, Coimbra, Portugal. (Ed. DX Viegas) Vol. 1, pp. 733–740. (ADAI, University of Coimbra)

Burgan R, Klaver R , Klaver J (1998) Fuel models and fire potential from satellite and surface observations. International Journal of Wildland Fire  8, 159–170.
Crossref | GoogleScholarGoogle Scholar | Cheney N (1981) Fire behaviour. In ‘Fire and the Australian Biota’. (Eds A Gill, R Groves, I Noble) pp. 151–175. (Australian Academy of Science: Canberra)

Cheney N, Sullivan A (1997) ‘Grassfires: Fuel, Weather and Fire Behaviour.’ (CSIRO Publishing: Melbourne)

Chou Y , Chase R (1993) Mapping probability of fire occurrence in San Jacinto mountains, California, USA. Environmental Management  17, 129–140.
Crossref | GoogleScholarGoogle Scholar | Daniel W (1978) ‘Applied non-parametric statistics.’ (Houghton Mifflin Company: Boston)

DSE (2006) Product description: Vicmap vegetation. Victorian Department of Sustainability and the Environment, Spatial Information Infrastructure Division. (Melbourne)

Duffy P, Epting J, Graham J, Rupp TS , McGuire AD (2007) Analysis of Alaskan burn severity using remotely sensed data. International Journal of Wildland Fire  16, 277–284.
Crossref | GoogleScholarGoogle Scholar | Leonard JE, Blanchi R, Leicester RH (2004) On the development of a risk-model for bushfire attack on housing. In ‘Proceedings of Risk Conference 2004 – Melbourne’. (Bushfire Cooperative Research Centre: Melbourne) Available at http://www.bushfirecrc.com/research/downloads/Risk2004-Jleonard.pdf [Verified 30 November 2009]

Linn R, Winterkamp J, Edminster C, Colman J , Smith W (2007) Coupled influences of topography and wind on wildland fire behaviour. International Journal of Wildland Fire  16, 183–195.
Crossref | GoogleScholarGoogle Scholar | Luke R, McArthur A (1978) ‘Bushfires in Australia.’ (Australian Government Publishing Service: Canberra)

Noble I, Barry G , Gill A (1980) McArthur’s fire danger meters expressed as equations. Australian Journal of Ecology  5, 201–203.
Crossref | GoogleScholarGoogle Scholar |

Preisler H, Brillinger D, Burgan R , Benoit J (2004) Probability based models for estimation of wildfire risk. International Journal of Wildland Fire  13, 133–142.
Crossref | GoogleScholarGoogle Scholar |

Taylor S , Alexander M (2006) Science, technology, and human factors in fire danger rating: the Canadian experience. International Journal of Wildland Fire  15, 121–135.
Crossref | GoogleScholarGoogle Scholar |

Wilson A , Ferguson I (1986) Predicting the probability of house survival during bushfires. Journal of Environmental Management  23, 259–270.


Wylie B, Meyer D, Tieszen L , Mannel S (2002) Satellite mapping of surface biophysical parameters at the biome scale over North American grasslands: a case study. Remote Sensing of Environment  79, 266–278.
Crossref | GoogleScholarGoogle Scholar |