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Fire behaviour prediction - modelling and testing


The development of applicable fire behaviour prediction models, based on sound physical principles and validated with well documented field data, is still a strong requirement in the field of forest fire management. INFLAME project brings together ten European teams, from six different countries, experienced in this field of research, to address the following objectives:
1. Use satellite and GIS based information to prepare input data in forest fire prediction models;

2. Develop, apply and test existing or new methods for wind flow, fire behaviour and smoke dispersion modelling, both at local and at global scale;
3. Collect field and laboratory data to validate the various models that are being used to estimate different properties of fire spread;

4. Integrate the results in a software system, to assist the research and operational activities.

The main effort of lNFLAME will be addressed at its second objective, that of developing existing models or methods and validating them in a comprehensive way. The prediction of wind field over complex topography shall be addressed as a first step for the prediction of the overall progress of the fire front. Fire behaviour modelling will be restricted to surface fire propagation regimes, that are the most common ones. Two deterministic approaches shall be followed to describe the spread of the fire front. Existing models will be incorporated for evaluation purposes, but an original modelling philosophy will be developed and implemented.
A statistical approach, that treats forest fires propagation as a chaotic process, shall also be examined and tested to assess its practical usefulness. Smoke dispersion at the short and long ranges shall be analysed taking into consideration the emission properties of the fire front and the wind field.
GIS shall be used to refer geographically distributed properties relevant to fire propagation, namely topography, vegetation cover, land use and fire prevention resources. Furthermore, GIS will provide the graphical environment and programming tools for the integration of the different modules. Extensive use of remote sensing shall be made to generate data for the input and validation processes. Field experiments shall be made in various regions to validate the remote sensed data, and the various models developed or tested in the project.

KEYWORDS: Forest Fire Modelling, Wind modelling, GIS, Remote sensing, Smoke dispersion, Integrate system

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Participants (10)