Probabilistic risk assessment for wildfires

David R. Brillinger; Haiganoush K. Preisler; John W. Benoit

doi:10.1002/env.768

Treesearch

Probabilistic risk assessment for wildfires

Formally Refereed

Authors:

David R. Brillinger, Haiganoush K. Preisler, John W. Benoit

Year:

2006

Type:

Scientific Journal

Station:

Pacific Southwest Research Station

DOI:

https://doi.org/10.1002/env.768

Source:

Environmetrics. 17(6): 623-633.

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Abstract

Forest fires are an important societal problem. They cause extensive damage and substantial funds are spent preparing for and fighting them. This work develops a stochastic model useful for probabilistic risk assessment, specifically to estimate chances of fires at a future time given explanatory variables. Questions of interest include: Are random effects needed in the risk model? and if yes, How is the analysis to be implemented? An exploratory data analysis approach is taken using both fixed and random effects models for data concerning the Federal Lands in the state of California during the period 2000-2003.

Keywords

biased sampling, false discovery rate, forest fires, generalized mixed model, penalized quasi-likelihood, risk

Citation

Brillinger, D. R.; Preisler, H. K.; Benoit, J. W. 2006. Probabilistic risk assessment for wildfires. Environmetrics. 17(6): 623-633. https://doi.org/10.1002/env.768.