Citation

Abid F. Fire Technol. 2021; 57(2): 559-590.

Copyright

(Copyright © 2021, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s10694-020-01056-z

PMID

unavailable

Abstract

Forest fires are one of the major environmental concerns, each year millions of hectares are destroyed over the world, causing economic and ecological damage as well as human lives. Thus, predicting such an environmental issue becomes a critical concern to mitigate this threat. Several technologies and new methods have been proposed to predict and detect forest fires. The trend is toward the integration of artificial intelligence to automate the prediction and detection of fire occurrence. This paper presents a comprehensive survey of the machine learning algorithms based forest fires prediction and detection systems. First, a brief introduction to the forest fire concern is given. Then, various methods and systems in forest fires prediction and detection systems are reviewed. Besides works that reported fire prediction and detection systems, studies that assessed the factors influencing the fire occurrence and risk are discussed. The main issues and outcomes within each study are presented and discussed.

Language: en

Keywords

Fire detection system; Fire prediction system; Forest fires; Logistic regression; Machine learning; Neural network