Three-Dimensional Dynamic Simulation System for Forest Surface Fire Spreading Prediction

Jianwei Li, Xiaowen Li, Chongchen Chen, Huiru Zheng, Naiyuan Liu

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Forest fire is one of the most frequent, fast spreading and destructive natural disasters. Many countries have developed their own fire prediction model and computational systems to predict the fire spreading, however, the user interaction, display effect and prediction accuracy have not yet met the requirements for firefighting in real forest fire events. The forest fire spreading is a complex process affected by multi-factors. Understanding the relationships between these multi-factors and the forest fire spreading trend is vital to predicting the fire spreading promptly and accurately to make the strategy in extinguishing the forest fire. In this paper, we propose and develop a three-dimensional (3D) forest fire spreading simulation system, FFSimulator, to visualize the impact of multi-factors to the fire spread. FFSimultor integrates the multi-factor analysis approach with the FARSITE prediction model to improve the prediction. The FFSimulator developed applies 3D scene organization, template-based vector data mapping and overlaps visualization techniques to provide a 3D dynamic visualization of large-scale forest fire. The 3D multi-factors superposition analysis simulates the impacts of individual factor and multi-factors on the trend of surface fire spreading, which can be used to identify the key sites for the prevention and the control of forest fires. The system has been tested and evaluated using real data of Shanghan forest fire.
LanguageEnglish
Article number32 (8)
Number of pages23
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume32
Issue number8
DOIs
Publication statusPublished - 16 Mar 2018

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Fires
Computer simulation
Factor analysis
Visualization
Disasters
Display devices

Keywords

  • Forest surface fire; fire spreading prediction; dynamic simulation and visualization; multi-factor analysis Read More: https://www.worldscientific.com/doi/abs/10.1142/S021800141850026X

Cite this

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title = "Three-Dimensional Dynamic Simulation System for Forest Surface Fire Spreading Prediction",
abstract = "Forest fire is one of the most frequent, fast spreading and destructive natural disasters. Many countries have developed their own fire prediction model and computational systems to predict the fire spreading, however, the user interaction, display effect and prediction accuracy have not yet met the requirements for firefighting in real forest fire events. The forest fire spreading is a complex process affected by multi-factors. Understanding the relationships between these multi-factors and the forest fire spreading trend is vital to predicting the fire spreading promptly and accurately to make the strategy in extinguishing the forest fire. In this paper, we propose and develop a three-dimensional (3D) forest fire spreading simulation system, FFSimulator, to visualize the impact of multi-factors to the fire spread. FFSimultor integrates the multi-factor analysis approach with the FARSITE prediction model to improve the prediction. The FFSimulator developed applies 3D scene organization, template-based vector data mapping and overlaps visualization techniques to provide a 3D dynamic visualization of large-scale forest fire. The 3D multi-factors superposition analysis simulates the impacts of individual factor and multi-factors on the trend of surface fire spreading, which can be used to identify the key sites for the prevention and the control of forest fires. The system has been tested and evaluated using real data of Shanghan forest fire.",
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Three-Dimensional Dynamic Simulation System for Forest Surface Fire Spreading Prediction. / Li, Jianwei; Li, Xiaowen; Chen, Chongchen; Zheng, Huiru; Liu, Naiyuan.

In: International Journal of Pattern Recognition and Artificial Intelligence, Vol. 32, No. 8, 32 (8), 16.03.2018.

Research output: Contribution to journalArticle

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