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Journal of Statistical Theory and Practice

, Volume 8, Issue 3, pp 509–533 | Cite as

Generating Annual Fire Risk Maps Using Bayesian Hierarchical Models

  • K. F. Turkman
  • M. A. Amaral Turkman
  • P. Pereira
  • A. Sá
  • J. M. C. Pereira
Article

Abstract

Vegetation fires are an important environmental and socioeconomic problem, and large budgets are spent in fire prevention and fire fighting. Detailed knowledge of spatiotemporal patterns of fire occurrence is required for effective and efficient fire management, and annual fire risk maps can be an important tool to support strategic decisions relating to location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence, without addressing the loss component. We propose and evaluate two alternative approaches to the development of annual fire risk maps, using an atlas of annual burned area maps of Portugal (1975–2009), derived from the classification of satellite imagery, and a set of environmental maps representing vegetation, climatic, and topographic covariates. We look at current approaches for producing annual fire risk maps, and suggest improvements by incorporating the strong spatial and temporal dependence that exists in the data. This is accomplished using two different modeling strategies. The first strategy consists of modeling interarrival times between fires using a discrete version of the Weibull model. The second strategy consists of modeling annual fire occurrences using a first-order nonhomogeneous Markov model. These two distinct strategies accommodate different possibilities to introduce time-dependent covariates and make complementary probabilistic statements.

Keywords

Fire frequency data Discrete Weibull model Non-homogeneous Markov models Spatio-temporal models 

AMS Subject Classification

62M30 62P12 

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Copyright information

© Grace Scientific Publishing 2014

Authors and Affiliations

  • K. F. Turkman
    • 1
  • M. A. Amaral Turkman
    • 1
  • P. Pereira
    • 1
    • 2
  • A. Sá
    • 3
  • J. M. C. Pereira
    • 3
  1. 1.CEAUL-FCULUniversity of LisbonLisbonPortugal
  2. 2.ESTSetubalPolytechnical Institute of SetúbalSetúbalPortugal
  3. 3.CEF and ISATechnical University of LisbonLisbonPortugal

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