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Gewählte Publikation:

Arndt, N; Vacik, H; Koch, V; Arpaci, A; Gossow, H.
(2013): Modeling human-caused forest fire ignition for assessing forest fire danger in Austria
IFOREST. 2013; 6: FullText FullText_BOKU

Forest fires have not been considered as a significant threat for mountain forests of the European Alpine Space so far. Climate change and its effects on nature, ecology, forest stand structure and composition, global changes according to demands of society and general trends in the provision of ecosystem services are potentially going to have a significant effect on fire ignition in the future. This makes the prediction of forest fire ignition essential for forest managers in order to establish an effective fire prevention system and to allocate fire fighting resources effectively, especially in alpine landscapes. This paper presents a modeling approach for predicting human-caused forest fire ignition by a range of socio-economic factors associated with an increasing forest fire danger in Austria. The relationship between touristic activities, infrastructure, agriculture and forestry and the spatial occurrence of forest fires have been studied over a 17-year period between 1993 and 2009 by means of logistic regression. Some 59 independent socio-economic variables have been analyzed with different models and validated with heterogeneous subsets of forest fire records. The variables included in the final model indicate that railroad, forest road and hiking trail density together with agricultural and forestry developments may contribute significantly to fire danger. The final model explains 60.5% of the causes of the fire events in the validation set and allows a solid prediction. Maps showing the fire danger classification allow identifying the most vulnerable forest areas in Austria and are used to predict the fire danger classes on municipality level.
Autor*innen der BOKU Wien:
Arpaci Alexander
Gossow Hartmut
Koch Valerie
Vacik Harald
BOKU Gendermonitor:

Find related publications in this database (Keywords)
Forest Fire
European Alpine Space
Socio-economic Factors
Geographic Information System
Logistic Regression

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