Environmental and Ecological Statistics

, Volume 17, Issue 1, pp 1–28

Spatial extremes of wildfire sizes: Bayesian hierarchical models for extremes


  • Jorge M. Mendes
  • Patrícia Cortés de Zea Bermudez
    • CEAUL, Faculty of SciencesUniversity of Lisbon
  • José Pereira
    • ISA-UTL
    • CEAUL, Faculty of SciencesUniversity of Lisbon
  • M. J. P. Vasconcelos
    • Tropical Research Institute

DOI: 10.1007/s10651-008-0099-3

Cite this article as:
Mendes, J.M., de Zea Bermudez, P.C., Pereira, J. et al. Environ Ecol Stat (2010) 17: 1. doi:10.1007/s10651-008-0099-3


In Portugal, due to the combination of climatological and ecological factors, large wildfires are a constant threat and due to their economic impact, a big policy issue. In order to organize efficient fire fighting capacity and resource management, correct quantification of the risk of large wildfires are needed. In this paper, we quantify the regional risk of large wildfire sizes, by fitting a Generalized Pareto distribution to excesses over a suitably chosen high threshold. Spatio-temporal variations are introduced into the model through model parameters with suitably chosen link functions. The inference on these models are carried using Bayesian Hierarchical Models and Markov chain Monte Carlo methods.


Bayesian hierarchical modelsGeneralized Pareto distributionSpatial and temporal processesMCMC

Copyright information

© Springer Science+Business Media, LLC 2008