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Gewählte Master / Diploma Thesis:

Nelson Grima (2011): Forest Fire Hazard Mapping in Carinthia (Southern Austria).
Master / Diploma Thesis - Institut für Waldbau (WALDBAU), BOKU-Universität für Bodenkultur, pp 64. UB BOKU obvsg

Data Source: ZID Abstracts
In Europe forest fires burn a large surface of land every year. In the Alpine region, though considered as a minor issue, fire burns an annual average of 20 000 ha, and the frequency and intensity of forest fires is expected to increase in the future. In order to improve the capacity of prevention and suppression of forest fires, the Alpine Forest Fire Warning System (ALP FFIRS) project was launched in 2009. As a contribution to that project, this work analyzes datasets from different sources, using geospatial analysis techniques, to calculate a Forest Fire Hazard. Different variables are combined to obtain an Integrated Danger Index for forest fires in the study area. These variables are the socioeconomic causes which drive the ignition of forest fires, the ignition of forest fires caused by lightning, the moisture content of the fine fuels in the forest, the fuel type, the slope of the relief, and the speed of the local winds. By integrating those factors in total 81 different models are generated, which are validated with the records available from a database of forest fires in the case study region. The validation process allowed a ranking for the models according to their capability to properly estimate the fire hazard for the given case study. A statistical analysis allowed to validate the model outputs for each scenario. The results show that in the scenarios where the moisture content of the fine fuels is high or medium, the danger of forest fires is explained by socioeconomic factors with some (but lower) influence of natural factors giving more importance to the ignition factor then to the propagation of forest fires. In a scenario where the moisture content of the fine fuels is low, the ignition factor has a lower relevance compared to the propagation factor. The best range of models is chosen to present fire hazard in the study area under different conditions. Based on the findings of the analysis recommendations for further improvements are made.

Beurteilende(r): Vacik Harald
1.Mitwirkender: Arpaci Alexander

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