Journal Article

EXPERIMENT AND RESEARCH ON PREDICTION MODEL OF FOREST FIRE SPREAD BASED ON ENSEMBLE KALMAN FILTER

Zhang, Shiyu, Li, Xingdong, Chen, Xiandong, Hua, Jun, Gao, Hewei, Liu, Jiuqing, Hu, Haiqing

2021

Overview

The spread of forest fire is an extremely complex and harmful natural phenomenon. At present, the forest fire spread model has some shortcomings, such as complex formula, inaccurate simulation value and so on. In this paper, the Ensemble Kalman Filter(ENKF) algorithm is applied to the field of forest fire spread so that it can better predict the spread of forest fire. Firstly, the Rothermel forest fire speed formula is simplified, and the simplified Rothermel speed value is modified by the actual measured forest fire spread speed value, so that the optimal model simulation value is obtained. Then the optimal speed is input into Cellular Automata(CA) to simulate the spread of forest fire. Secondly, the experiment is carried out by changing the slope, bed thickness, moisture content, load and wind speed. And the actual measured speed value, the simplified Rothermel model value and the optimized value after ENKF are compared in the process of fire spread. Finally, The experimental results show that the error of fire spread speed corrected by ENKF is smaller, the forest fire spread contour obtained from the optimal speed value by ENKF is closer to the actual fire spread contour, and the highest similarity index is 0.854. The model proposed in this paper has the ability to predict the spread of forest fire indoors.

• Publisher: The MCFNS Publisher
• Subject: Algorithms / Automata theory / Bed load / Cellular automata / Contours / Data assimilation / Error correction / Experiments / Forest fires / Forest management / Forestry / Forests / Kalman filters / Laboratories / Moisture content / Prediction models / Simulation / Water content / Wind speed