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Application of advanced clusteringmethods in a GIS based forest fire risk assessment tool

Gobakis Konstantinos, Lykas Christos, Kolokotsa Dionysia, Stavrakakis Georgios

Πλήρης Εγγραφή

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Περίληψη

In recent years the forest fire risk management practices tend to a convergenceboth in Europe and worldwide. The majority of countries in Europe and especially in theMediterranean area adopt various indices for the fire risk assessment. The aim of the presentpaper is to describe a GIS based Informative System for the dynamic assessment of the forestfires risk through the use of forest fire risk assessment indicators where meteorological andclimate parameters are incorporated. The fire risk index developed combines the Fire HazardIndex (FHI) which is a measure the fire initiation danger attributed to flammable fuels and to theforest topology with the Fire Danger Index (FDI) which indicates the possibility of forest fireignition based on meteorological parameters. The aforementioned indices provide an indicationof the fire risk on a five scale categorization ranging from 0 (no fire danger) to 5 (increased firedanger). These five classes are usually defined by experts in a heuristic way. In the present paperadvanced clustering techniques for the fire risk index classification are developed and tested. Theclustering techniques tested are Fuzzy, K means and Gaussian. The clustering techniques whichare incorporated in a GIS based Information System which provides the necessary informationon-line

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