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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Main Authors: Arndt N, Vacik H, Koch V, Arpaci A, Gossow H
Format: Article
Language:English
Published: Italian Society of Silviculture and Forest Ecology (SISEF) 2013-12-01
Series:iForest - Biogeosciences and Forestry
Subjects:
Online Access:https://iforest.sisef.org/contents/?id=ifor0936-006
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spelling 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
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