Response time assessment in forest fire spread simulation: An integrated methodology for efficient exploitation of available prediction time

Andrés Cencerrado, Ana Cortés, Tomàs Margalef

Research output: Contribution to journalArticleResearchpeer-review

16 Citations (Scopus)

Abstract

This work details a framework developed to shorten the time needed to perform fire spread predictions. The methodology presented relies on a two-stage prediction strategy which introduces a calibration stage in order to relieve the effects of uncertainty on simulator input parameters. Early assessment of the response time and quality of the results obtained constitute a key component in this method. This automatic and intelligent process of identification of lengthy simulations that slow down the course of the predictions presents a very high hit ratio. However, discarding certain simulations from the adjustment process (based on evolutionary algorithms) could lead to loss of accuracy in our predictions. A strong statistical study to analyze the impact of this action on our final predictions is reported. This study is based on a real fire which burnt 13,000ha in the region of Catalonia (north-east of Spain) in the summer of 2012. © 2014 Elsevier Ltd.
Original languageEnglish
Pages (from-to)153-164
JournalEnvironmental Modelling and Software
Volume54
DOIs
Publication statusPublished - 1 Feb 2014

Keywords

  • Data uncertainty
  • Decision trees
  • Fire spread prediction
  • Genetic algorithms
  • High performance computing
  • Prediction framework

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