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7th Workshop on Forest Fire Management - EARSeL, European ...

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48<br />

I - PRE-FIRE PLANNING AND MANAGEMENT<br />

moves towards the crests, the intensity of fire is decreasing due to the<br />

absence of trees.<br />

3.2 - Advantages and problems of the fire risk built model<br />

The established model with 5 factors has defined a map of fire intesity with<br />

eight classes. Such a map was unavailable in the study area, although at<br />

this stage the map still depends <strong>on</strong> relatively subjective procedures. The<br />

map represents the result of modelling from available knowledge and data,<br />

can serve needs of different researchers, and is important for policies and<br />

socio-ec<strong>on</strong>omic decisi<strong>on</strong>-makers. It can prioritize the anti-fire protecti<strong>on</strong><br />

measures according to the obtained fire risk level. The model has certain<br />

advantages over fully-automated fire risk models which are too-data hungry<br />

to be applied at a regi<strong>on</strong>al scale. This model can be easily extrapolated<br />

to all the country if the functi<strong>on</strong>al capacities of GIS are used, because<br />

they allow model integrati<strong>on</strong> with additi<strong>on</strong>al basic and factorial data and<br />

code modificati<strong>on</strong> in order to analyse the data. The factorial morphological<br />

maps (slope gradient and slope aspect) are more persistent with time than<br />

the other used maps, i.e. land cover/use, urban expansi<strong>on</strong> and proximity to<br />

road network which must be updated and can change drastically through<br />

years due to human activities. However, many difficulties have been<br />

encountered. The use of <strong>on</strong>e-lumped value for land cover/use in fire risk<br />

modelling is sometimes an oversimplificati<strong>on</strong> of the real situati<strong>on</strong> in which<br />

fire shows complex spatial and temporal patterns. Future study should focus<br />

<strong>on</strong> parameters [e.g., fuel loading (kg/m 2 ), surface to volume ratio, fuel<br />

moisture c<strong>on</strong>tent, fuel bed depth, particle density (kg/m 3 ), etc.] and methods<br />

to capture this variability and to incorporate data in fire risk models.<br />

References<br />

B<strong>on</strong>azountas, M., Kallidromitou, D., Kassomenos, P., 2006. A decisi<strong>on</strong> support<br />

system for managing forest fire casualties. Journal of Envir<strong>on</strong>mental<br />

<strong>Management</strong>, 84, 412-418.<br />

ICONA, 1992. Los incendios forestales en Espana durante 1991. Instituto<br />

Naci<strong>on</strong>al para la C<strong>on</strong>versaci<strong>on</strong> de la Naturaleza, MAPA, Madrid.<br />

LNCSR-LMoA, 2002. Land cover/use maps of Leban<strong>on</strong> at 1:20,000 scale.<br />

Lebanese Nati<strong>on</strong>al Council for Scientific Research-Lebanese Ministry of<br />

Agriculture.<br />

Mitri, G.H., Gitas, I.Z., 2004. A semi-automated object oriented model for<br />

burned area mapping in the Mediterranean regi<strong>on</strong> using Landsat-TM<br />

imagery. Internati<strong>on</strong>al Journal of Wildland <strong>Fire</strong>, 13, 367-376.<br />

Weise, D.R, Biging, G.S., 1997. A qualitative comparis<strong>on</strong> of fire spread models<br />

incorporating wind and slope effects. <strong>Forest</strong> Science, 43(2), 170-180.

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