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

FUEL MODEL MAPPING USING IKONOS IMAGERY TO SUPPORT SPATIALLY
EXPLICIT FIRE SIMULATORS
B. Arca 1
V. Bacciu 2, 3 , G. Pellizzaro 1, 3 , M. Salis 2, 3 , A. Ventura 1, 3 ,
P. Duce 1, 3 , D. Spano 2, 3 , G. Brundu 4
1 Istituto di Biometeorologia, National Research Council,
Sassari, Italy, B.Arca@ibimet.cnr.it
2 Department of Economics and Woody Plant Ecosystems (DESA), University of Sassari, Italy
3 Euro-Mediterranean Center on Climate Change (CMCC), Italy
4 Corpo Forestale della Regione Sardegna, Italy
Abstract: The effect of fire environment on fire spread and behaviour can
be adequately simulated by using different models, mainly based on semiphysical
approaches. Effects on fire behaviour can be integrated at various
scales using spatially and temporally explicit fire spread and behaviour simulators.
Criticisms of fire simulators frequently concern the need of high
resolution environmental data, in particular data on fuel types, fuel model
characteristics and weather variables. The aim of this work was to evaluate
the capabilities of IKONOS imagery to accurately map fuel types and fuel
model for the main Mediterranean maquis associations in Northern Sardinia
(Italy). We also evaluated the sensitivity of the predicted fire spread and
fire behaviour to variation in spatial resolution of fuel model maps. The
results showed a sensitivity of the predicted burned areas and rate of
spread to the accuracy and resolution of fuel model maps, providing a clear
insight for the use of fire simulators in fire management applications.
1 - Introduction
The availability of accurate fuel data at different spatial and temporal
scales is essential for fire management applications. A reasonable prediction
of fire potential can help fire managers in planning and prioritizing
activities and in both fire hazard and fire risk assessment. Fuel physical
characteristics related to different fuel complexes are frequently parameterized
into “fuel models”. Fuel model maps are generally supplied as inputs
to spatially explicit fire simulators to achieve fire spread and behaviour
information for fuel management and fire management applications. To
obtain realistic simulations of fire spread and behaviour, fuel maps must be
developed at fine resolutions. In this context, the use of remotely sensed
multispectral data can be successfully adopted to develop fuel maps at local
scale. Recently, the availability of high spatial and spectral satellite data
has provided useful tools for capturing fine scale fuel distribution. In this
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