title: Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.
abstract: Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.
authors.affiliation: Department of Natural Resources, Isfahan University of Technology, Isfahan, 84156-83111, Iran. hbashari@cc.iut.ac.ir.
authors.forename: Hossein
authors.initials: H
authors.lastname: Bashari
authors.affiliation: Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, 88186-34141, Iran.
authors.forename: Ali Asghar
authors.initials: AA
authors.lastname: Naghipour
authors.affiliation: Department of Natural Resources, Isfahan University of Technology, Isfahan, 84156-83111, Iran.
authors.forename: Seyed Jamaleddin
authors.initials: SJ
authors.lastname: Khajeddin
authors.affiliation: Department of Natural Resources, Isfahan University of Technology, Isfahan, 84156-83111, Iran.
authors.forename: Hamed
authors.initials: H
authors.lastname: Sangoony
authors.affiliation: Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, 88186-34141, Iran.
authors.forename: Pejman
authors.initials: P
authors.lastname: Tahmasebi
mesh_terms: D001499:Bayes Theorem; D017753:Ecosystem; D005390:Fires; D007492:Iran; D008962:Models, Theoretical; D018570:Risk Assessment; D035501:Uncertainty
keywords: Arid and semi-arid ecosystems; Bayesian belief network; Diagnostic; Prediction; Uncertainty