DocumentCode :
2724725
Title :
An analytical review on the most widely used meteorological models in forest fire prediction
Author :
Hamadeh, Nizar ; Hilal, Alaa ; Daya, Bassam ; Chauvet, Pierre
Author_Institution :
LARIS EA, Univ. of Angers, Angers, France
fYear :
2015
fDate :
April 29 2015-May 1 2015
Firstpage :
239
Lastpage :
244
Abstract :
At the beginning of 20th century, scientists started to develop mathematical models in order to predict the probability of occurrence of forest fires. Meteorological parameters, such as daily temperature and humidity, were mainly used. In this paper, we review the seven most usable fire prediction indices in the world, that are Angstrom, Keetch-Byram, Modified Keetch-Byram, Canadian fire weather index, Nesterov, Modified Netserov, and Baumgartner Index. A comparative study including the mathematical equations, properties, characteristics, performance and field of application of each model is presented. The different developed models were optimized to the local characteristics of the place of study. The problematic of suitability and compliance of indices in other regions with different conditions is discussed. Recent initiatives are finally presented.
Keywords :
atmospheric humidity; atmospheric temperature; geophysical techniques; probability; wildfires; Angstrom index; Canadian fire weather index; daily humidity; daily temperature; forest fire prediction indices; mathematical equations; mathematical models; meteorological models; meteorological parameters; modified Keetch-Byram index; occurrence probability; scientists; Fires; Fuels; Indexes; Mathematical model; Meteorology; Moisture; Soil; fire weather indices; forest fire prediction; limitations and transferability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2015 Third International Conference on
Conference_Location :
Beirut
Print_ISBN :
978-1-4799-5679-1
Type :
conf
DOI :
10.1109/TAEECE.2015.7113633
Filename :
7113633
Link To Document :
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