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

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I - PRE-FIRE PLANNING AND MANAGEMENT
will then be applied to the other European countries, making the necessary
adjustments to cope with the specific conditions of each area.
1 - The European Forest Fire Information System (EFFIS)
Since 2000, the European Forest Fire Information System supports the forest
fire services of the EU countries in forest fire prevention and management.
EFFIS is a web-based system that provides reliable and updated information
on several issues related to wildland fires in Europe, such as mapping
of burnt areas, identification of hotspots and fire danger forecast.
The fire danger maps provided by EFFIS follow a dynamic and short-term
approach, based on meteorological variables, and are being mainly used in
the pre-suppression and suppression phases.
Further improvements of EFFIS, currently under development, are intended
to include information on long term forest fire risk at the European scale.
Long term forest fire risk will allow the assessment of the vulnerability of
forested/wildland areas to fire, the analysis of the probability of occurrence
and of the potential fire behaviour in case of ignition.
2 - Long term forest fire risk: first steps in modelling forest fire ignition
2.1 - The European Fire Database
The European Fire Database was established in 2000, on the basis of the
pre-existing database referred to as “common core of information on forest
fires” that was set up in the context of the first EU Regulation on forest
fire prevention established in 1992. It currently includes data of 21 countries,
about 1.87 million individual fire event records. The European
Mediterranean countries have the longest series of fire data, starting from
1980 (Portugal), 1983 (Greece) and 1985 (Spain, Italy, France). Most of the
fire ignition points are provided with a descriptive location based on the
administrative districts of each country. Only in recent years geographical
coordinates have been added to the database.
2.1 - Location of ignition points (IP)
Since most of the ignition points in the database lack an accurate geo-location,
it is necessary to estimate the spatial distribution of ignition points.
One of the possible approaches is the random distribution of the number of
ignition points in the wildland area of each administrative division, selected
through Corine Land Cover (Amatulli et al., 2007, de la Riva et al.,
2004), followed by the application of a kernel density estimation method.