Forest fire spread model based on the grey system theory

Abstract

Accurate prediction of forest fire spread is very essential for minimizing its effects. Although many models have been developed to predict the forest fire spread, all these models require several parameters, sometimes, cannot be obtained in a real time. In this paper, the grey system theory was applied for forest fire spread model developing. By preprocessing and fusing the MODIS remote sensing data, the sequence data of the grey model can be confirmed. After making precision comparison among least square estimation algorithm, least square interpolation algorithm and ER algorithm, forest fire spread GM(1, 1) model was developed with ER algorithm and precision of the model was evaluated at the same time. The results showed that the fitting precision and predicting precision of the model were both high, of which the one-level model made up 50%, the two-level 25% and the model between the one-level and the two-level 25%. The prediction accuracy of forest fire spreading model was tested to meet the requirement of modeling. GM(1, 1) model provided a new approach for the study of forest fire spread simulation.