• DocumentCode
    1762748
  • Title

    Mountains Forest Fire Spread Simulator Based on Geo-Cellular Automaton Combined With Wang Zhengfei Velocity Model

  • Author

    Tao Sun ; Linghan Zhang ; Wangli Chen ; Xianxiu Tang ; Qianqing Qin

  • Author_Institution
    Electron. Inf. Sch., Wuhan Univ., Wuhan, China
  • Volume
    6
  • Issue
    4
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    1971
  • Lastpage
    1987
  • Abstract
    The aim of this paper is to propose a more practical mountain fire spread model for fire behavior prediction and management in Southwest forest area of China. These areas are covered mainly with spatial heterogeneous flammable forest and are characterized by undulating terrain and steep slopes. This model can produce more accurate fire propagation maps by combining CA (Cellular Automaton) framework with Wang Zhengfei fire physical velocity model in fine scale. Considering the inherent uncertainties of fire propagation, the model has been built on multi-dimension geophysical and environmental components and also sound knowledge of fire spread physical mechanism. Regarding small fuel patches as spatial homogenous cells, this approach makes it easier to generate higher level complex fire behavior maps from CA simple local rules and local behavior integrated with high resolution vegetation images, fine scale terrain maps and surface wind field. Because the model focuses primarily on the study of surface fire front propagation behavior, it attempts to simplify complex fuel modeling. Additionally, this Wang-Geophysical-CA model is able to analyze the time series spatial pattern of fire-front spread and model local behavior instead of the final fire spread pattern of the conventional approach. In this work, not only single influence verification tests have been made, but also simulation tests with multiple influences are carried out to demonstrate the capability of the model with fine scale vegetation maps, surface wind field, terrain, moisture content and man-made structures. Consequently, it is believable that the model predictions are in good agreement with experimental data for steady-state fire simulation. The proposed model helps to gain a greater understanding of the fire front spread local behavior and can quickly generate a sequence of complex fire front contours. It enables local managers to plan practical fire prevention activities in Southwest forest area of C- ina as well as improve fire management skills, and will enhance the effectiveness of fire fighting strategies.
  • Keywords
    cellular automata; terrain mapping; vegetation; wildfires; China; Southwest forest area; Wang Zhengfei velocity model; Wang-Geophysical-CA model; cellular automaton framework; complex fire front contours; fine scale terrain maps; fine scale vegetation maps; fire propagation uncertainties; geo-cellular automaton; high resolution vegetation images; mountain fire spread model; mountains forest fire spread simulator; spatial heterogeneous flammable forest; surface fire front propagation behavior; surface wind field; Computational modeling; Fuels; Mathematical model; Moisture; Predictive models; Remote sensing; Uncertainty; Fine scale; Wang Zhengfei physical velocity model; geo-cellular automaton; local rules;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2012.2231956
  • Filename
    6387632