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

FIRST STEPS TOWARDS A LONG TERM FOREST FIRE RISK OF EUROPE
S. Oliveira, A. Camia & J. San-Miguel
Joint Research Centre of the European Commission,
Institute for Environment and Sustainability, Ispra (VA), Italy
sandra.santos-de-oliveira@jrc.ec.europa.eu; andrea.camia@jrc.ec.europa.eu;
jesus.san-miguel@jrc.ec.europa.eu
Abstract: Forest fires are a major disturbance in Europe, particularly in the
Mediterranean region. Long term forest fire risk assessment is an important
tool for supporting the responsible authorities in setting up suitable fireprevention
measures and allocating fire-fighting resources. This work provides
the current status of a research effort aimed at developing a long
term fire risk map of Europe, which will be included as a component of the
European Forest Fire Information System (EFFIS). The fire risk model adopted
for the assessment is based on the approach that combines fire occurrence
and fire outcome, thus encompassing probability of ignition, estimated
fire behavior and expected consequences, and aiming to integrate
physical, biological and socio-economic factors.
The first step has been the enhancement of the fire occurrence data stored
in the European Fire Database of EFFIS, in which recorded fire ignitions
exhibit a certain degree of geo-location uncertainty. Location of fire ignition
points is given in most cases as administrative district without geographical
coordinates. Therefore methods to approximate density estimations
of the spatial distribution of fire ignition points are needed. One of
the options tested in this study is the use of land cover data to constrain
the geo-location of the ignition points recorded in a given administrative
district inside the boundaries of the fire spatial domain (i.e. forested and
wildland areas). The point distribution is made randomly or with a weighted
probability filtering, and a continuous surface is then created by kernel
density methods.
A second step is the analysis of potential variables affecting fire occurrence.
The list of these variables is being compiled on the basis of extensive
literature review and experts’ knowledge. The final selection of the
variables to be used in the model will be based on data availability and
exploratory statistical analysis. To assess the significance of the predictor
variables in fire occurrence, several alternative methods are being explored,
among which are logistic regression and geographically weighted regression.
The methodology firstly developed for the Euro-Mediterranean region
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