Modeling human-caused forest fire ignition for assessing forest fire danger in Austria
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 eco...
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Italian Society of Silviculture and Forest Ecology (SISEF)
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doaj-3e6a7e1c43074dc9816b42bf0810f1382020-11-24T21:39:39ZengItalian Society of Silviculture and Forest Ecology (SISEF)iForest - Biogeosciences and Forestry1971-74581971-74582013-12-016131532510.3832/ifor0936-006936Modeling human-caused forest fire ignition for assessing forest fire danger in AustriaArndt N0Vacik H1Koch V2Arpaci A3Gossow H4Department of Forest and Soil Sciences, Institute of Silviculture, University of Natural Resources and Life Sciences, Peter Jordan Str. 82, A-1190 Vienna (Austria)Department of Forest and Soil Sciences, Institute of Silviculture, University of Natural Resources and Life Sciences, Peter Jordan Str. 82, A-1190 Vienna (Austria)Department of Landscape, Spatial and Infrastructure Sciences, Institute of Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences, Peter Jordan Str. 82, A-1190 Vienna (Austria)Department of Forest and Soil Sciences, Institute of Silviculture, University of Natural Resources and Life Sciences, Peter Jordan Str. 82, A-1190 Vienna (Austria)Department of Integrative Biology and Biodiversity Research, Institute of Wildlife Biology and Game Management, University of Natural Resources and Life Sciences, Peter Jordan Str. 82, A-1190 Vienna (Austria)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 modelling 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. 59 independent socio-economic variables have been analysed 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.https://iforest.sisef.org/contents/?id=ifor0936-006Forest FireEuropean Alpine SpaceAustriaInfrastructureSocio-economic FactorsGeographic Information SystemLogistic Regression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arndt N Vacik H Koch V Arpaci A Gossow H |
spellingShingle |
Arndt N Vacik H Koch V Arpaci A Gossow H Modeling human-caused forest fire ignition for assessing forest fire danger in Austria iForest - Biogeosciences and Forestry Forest Fire European Alpine Space Austria Infrastructure Socio-economic Factors Geographic Information System Logistic Regression |
author_facet |
Arndt N Vacik H Koch V Arpaci A Gossow H |
author_sort |
Arndt N |
title |
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria |
title_short |
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria |
title_full |
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria |
title_fullStr |
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria |
title_full_unstemmed |
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria |
title_sort |
modeling human-caused forest fire ignition for assessing forest fire danger in austria |
publisher |
Italian Society of Silviculture and Forest Ecology (SISEF) |
series |
iForest - Biogeosciences and Forestry |
issn |
1971-7458 1971-7458 |
publishDate |
2013-12-01 |
description |
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 modelling 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. 59 independent socio-economic variables have been analysed 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. |
topic |
Forest Fire European Alpine Space Austria Infrastructure Socio-economic Factors Geographic Information System Logistic Regression |
url |
https://iforest.sisef.org/contents/?id=ifor0936-006 |
work_keys_str_mv |
AT arndtn modelinghumancausedforestfireignitionforassessingforestfiredangerinaustria AT vacikh modelinghumancausedforestfireignitionforassessingforestfiredangerinaustria AT kochv modelinghumancausedforestfireignitionforassessingforestfiredangerinaustria AT arpacia modelinghumancausedforestfireignitionforassessingforestfiredangerinaustria AT gossowh modelinghumancausedforestfireignitionforassessingforestfiredangerinaustria |
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