A Survey of Machine Learning Algorithms Based Forest Fires Prediction and Detection Systems
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A Survey of Machine Learning Algorithms Based Forest Fires Prediction and Detection Systems Faroudja Abid *, Centre de De´veloppement des Technologies Avance´es, Cite´ 20 aouˆt 1956, Baba Hassen, Algiers, Algeria Received: 30 January 2020/Accepted: 21 October 2020
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. Keywords: Forest fires, Fire detection system, Fire prediction system, Logistic regression, Machine learning, Neural network
1. Introduction Forests [1] play a crucial role in the earth’s ecological balance. However, these natural resources are threatened by fires, which are related to natural and human factors. Forest fire [2, 3] is a disaster that entails considerable negative effects on natural environment, economic and human resources. The global warming and the threat of flora and fauna species lives are the forest fires consequences. Considering the threat caused by forest fires, early fire prediction and detection are important measures that significantly reduce damages caused by this disaster and reduce firefighting efforts. The first measure of the fire management is the forest fires prediction that concerns basically, the forest fire occurrence prediction, i.e., forecasting the forest fire outbreak probability before its initial ignition; by modeling the relationship between the fire risk and the influential factors such as weather conditions or fuel content. The main objective is to predict when and * Correspondence should be addressed to: Faroudja Abid, E-mail: [email protected]
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Fire Technology 2020 where the fire can occur to ovoid its ignition and spread. The prediction can also be considered after the initial-fire ignition; in this case the issue is about predicting the behavior of the forest fire, i.e., forecasting the fire spread evolution. The forest fire behavior prediction concerns the level of variability according to the fire environment (weather conditions, moisture content, fuel content and even human presences). For example the forest fires time-resolved spatial evolution prediction and the fire spread rate prediction with respect to the wind speed. In
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