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

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I - PRE-FIRE PLANNING AND MANAGEMENT
study, we explored the use of IKONOS data to develop fine resolution fuel
maps. We also evaluated the potential of the fuel model maps for predicting
fire spread and behaviour using spatially and temporal explicit fire simulators.
The general aim of this work was to evaluate the capabilities of
IKONOS imagery to accurately map fuel types and fuel model for main
Mediterranean maquis associations in Northern Sardinia (Italy).
2 - Materials and methods
The study was conducted in North-West Sardinia. The one-point stratified
sampling was adopted to identify the sampling sites for the estimation of
fuel load and other fuel model characteristics by destructive measurements.
Sampling sites were selected from the analysis of the Corine Land Cover
map, the IKONOS satellite images of the area, and the map of the potential
vegetation. The following variables were collected at each sampling site:
live and dead fuel load, depth of the fuel layer, plant cover. Dead and live
fuel load were inventoried following the standardized classes (1h, 10h,
100h) of the USDA National Fire-Danger Rating System. A cluster analysis
was applied to classify the different sites in terms of fuel types and the
results were reclassified using an adaptation of Prometheus classification
system. A supervised classification by the Maximum Likelihood algorithm
was performed on IKONOS images to identify and map the different types
of maquis vegetation. The sample of ground truth points used for training
the algorithm and validating the accuracy consisted of 132 points collected
by destructive measurements, non destructive measurements, and data
provided by visual classification of IKONOS images. The accuracy of the
classification was evaluated using the following statistical indicators
derived from an error matrix: overall accuracy, user’s accuracy, producer’s
accuracy, and Cohen’s kappa coefficient. Custom fuel models were associated
to each vegetation type to obtain fuel model map. This derived map was
re-sampled by the nearest neighbour algorithm using three different resolutions
(5m, 10m, 15m), and then used into the FARSITE fire area simulator
(Finney, 2004) to estimate the effect of the spatial resolution of fuel
maps on fire spread and behaviour.
3 - Results and discussion
The custom fuel models derived by both the cluster analysis and
Prometheus classification system are presented in Table 1. The total fuel
load and the fuel load of different fuel size classes data result similar to,
experimental data obtained in other studies conducted on shrubland vegetation.
Fuel model CM4 appears quite similar to fuel model FM4 (35.93 Mg
ha -1 ; Anderson, 1992) and fuel model SH7 (32.28; Scott and Burgan, 2005).
The ICONA fuel model key (1990) and Dimitrakopoulos (2002) provided data