Dynamic Data-driven Research on Forest Fire Behavior Overview

Abstract

In recent years, under the combined effects of climate change and El Niño, extreme weather has been occurring frequently, and natural disasters of all kinds have been increasing. Forest fire is the first of the three major natural disasters in forests, to reduce the possibility of starting forest fires, reduce the damage caused by forest fire disasters, as well as to predict the development trend of forest fires and fight them scientifically, we should systematically and scientifically grasp the law of forest fire occurrence and development. This paper analyses the various influencing factors affecting the behavior of forest fires and classifies meteorological factors and the moisture content of combustible materials as dynamic factors, and topographical factors and other factors of combustible materials except moisture content as slow-change factors. The research on dynamic data-driven forest fire behavior in recent years is reviewed, the advantages of dynamic data-driven technology for simulating fires are analyzed, the constraints of the technology are indicated, and the future development trend is shown.