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Analysis of factors influencing deployment of fire suppression resources in Spain using artificial neural networks

Sergi Costafreda-Aumedes (1), Adrian Cardil (2), Domingo M Molina (2), Sarah N Daniel (3), Robert Mavsar (4), Cristina Vega-Garcia (1)   

iForest - Biogeosciences and Forestry, Volume 9, Issue 1, Pages 138-145 (2015)
doi: https://doi.org/10.3832/ifor1329-008
Published: Jul 19, 2015 - Copyright © 2015 SISEF

Research Articles


In Spain, the established fire control policy states that all fires must be controlled and put out as soon as possible. Though budgets have not restricted operations until recently, we still experience large fires and we often face multiple-fire situations. Furthermore, fire conditions are expected to worsen in the future and budgets are expected to drop. To optimize the deployment of firefighting resources, we must gain insights into the factors affecting how it is conducted. We analyzed the national data base of historical fire records in Spain for patterns of deployment of fire suppression resources for large fires. We used artificial neural networks to model the relationships between the daily fire load, fire duration, fire type, fire size and response time, and the personnel and terrestrial and aerial units deployed for each fire in the period 1998-2008. Most of the models highlighted the positive correlation of burned area and fire duration with the number of resources assigned to each fire and some highlighted the negative influence of daily fire load. We found evidence suggesting that firefighting resources in Spain may already be under duress in their compliance with Spain’s current full suppression policy.

  Keywords


Fire Management, Neural Networks, Regional Models, Suppression Resources, Wildfire

Authors’ address

(1)
Sergi Costafreda-Aumedes
Cristina Vega-Garcia
Agriculture and Forest Engineering Department, University of Lleida, Alcalde Rovira Roure 191, 25198, Lleida (Spain)
(2)
Adrian Cardil
Domingo M Molina
Department of Crop and Forest Sciences, University of Lleida, Alcalde Rovira Roure 191, 25198, Lleida (Spain)
(3)
Sarah N Daniel
Agriculture and Environment Department, YMCA-Lebanon, Delta Center, 3rd floor - Horsh Tabet, Sin El Fil, 55570, Beirut (Lebanon)
(4)
Robert Mavsar
European Forest Institute (EFI), Yliopistokatu 6, 80100 Joensuu (Finland)

Corresponding author

 
Cristina Vega-Garcia
cvega@eagrof.udl.es

Citation

Costafreda-Aumedes S, Cardil A, Molina DM, Daniel SN, Mavsar R, Vega-Garcia C (2015). Analysis of factors influencing deployment of fire suppression resources in Spain using artificial neural networks. iForest 9: 138-145. - doi: 10.3832/ifor1329-008

Academic Editor

Davide Ascoli

Paper history

Received: Apr 29, 2014
Accepted: Mar 24, 2015

First online: Jul 19, 2015
Publication Date: Feb 21, 2016
Publication Time: 3.90 months

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