Assessment method for predicting occurrence risk of forest fires of further time phases

Abstract

The invention provides an assessment method for predicting the occurrence risk of forest fires of further time phases, and relates to assessment methods for the occurrence risk of fires. The method comprises steps of performing model training by selecting the vegetation data and the topographic data of the Nth time phase before the forest fire occurrence time phase and the meteorological data of the time phase where the forest fire occurrence time phase is, acquiring the relationship between the above data and the occurrence risk of a forest fire, and placing the real-time vegetation data andterrain data and the weather forecast data of the Nth time phase after the real-time time phase into the above relationship for assessment. The assessment method of the invention comprehensively considers a plurality of factors which induce the occurrence of forest fires, eliminates the bias of considering only meteorological factors to obtain assessment results, and realizes the fire risk assessment of large-scale and high spatial resolution due to the innovation of data selection. The assessment results are predictive, can provide a scientific basis for preventing forest fires and improvingprevention and control and disaster reduction systems, and help guide the prevention and control of forest fires.

Description

technical field [0001] The invention belongs to the technical field of fire risk assessment methods, and in particular relates to an assessment method for predicting forest fire risk in future phases. Background technique [0002] Forest fire is a very common and extremely destructive natural disaster. There are more than 200,000 forest fires in the world every year on average, and the burned forest area accounts for more than 1‰ of the total forest area in the world. On average, more than 10,000 forest fires occur in China every year, burning hundreds of thousands to millions of hectares of forests, accounting for about 5-8 per thousand of the country's forest area. Forest fires not only kill and injure forest trees, directly reduce forest area, but also seriously damage forest structure and forest environment, leading to the loss of forest ecosystem, forest biomass decline, and even human and livestock casualties. [0003] Although forest fires cannot be completely elimin...

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Problems solved by technology

[0005] In view of the foregoing, the purpose of the present invention is to: address the problems of single consideration factors, low spatial resolution, inability to predict the risk of forest fires in future phases and low assessment accuracy in existing forest fire risk assessment methods, and provide a method based on Multi-source remote sensing data can realize a large-scale, high-spatial resolution, and predictive forest fire risk assessment method

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