Wildland fire risk maps using S<sup>2</sup>F<sup>2</sup>M<sup>*</sup>
Wildland fires are a critical natural hazard in many regions of the World. Every year, millions of hectares are burned in Tropical, Boreal and Mediterranean forest, which causes a wide variety of effects, from atmospheric emissions, to soil erosion, biodiversity loss and drainage alterations. Reduct...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2005-12-01
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| Series: | Journal of Computer Science and Technology |
| Subjects: | |
| Online Access: | https://journal.info.unlp.edu.ar/JCST/article/view/843 |
| Summary: | Wildland fires are a critical natural hazard in many regions of the World. Every year, millions of hectares are burned in Tropical, Boreal and Mediterranean forest, which causes a wide variety of effects, from atmospheric emissions, to soil erosion, biodiversity loss and drainage alterations. Reduction of those negative effects of fire requires to improve current fire risk assessment methods. Wildland firerisk assessment is a very significant issue. This risk assessment is usually based on ignition probability due to meteorological or human factors, but it does not usually consider propagation danger when a wildland fire has started. To evaluate propagation danger, it is necessary to apply some propagation model and simulate the behaviour of the fireline. However, this propagation danger must be evaluated considering many different possible scenarios. Therefore, the amount of simulations that must be carried out is enormous and it is necessary to apply high-performance computing techniques to make the methodology feasible. In this paper, a method for creating propagation danger maps based on factorial experimentation is described. The methodology was applied at a southern Europe scale during the 2004 summer season. |
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| ISSN: | 1666-6046 1666-6038 |