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dc.contributor.authorCostafreda Aumedes, Sergi
dc.contributor.authorComas Rodríguez, Carles
dc.contributor.authorVega García, Cristina
dc.description.abstractThe increasing global concern about wildfires, mostly caused by people, has triggered the development of human-caused fire occurrence models in many countries. The premise is that better knowledge of the underlying factors is critical for many fire management purposes, such as operational decision-making in suppression and strategic prevention planning, or guidance on forest and land-use policies. However, the explanatory and predictive capacity of fire occurrence models is not yet widely applied to the management of forests, fires or emergencies. In this article, we analyse the developments in the field of human-caused fire occurrence modelling with the aim of identifying the most appropriate variables and methods for applications in forest and fire management and civil protection. We stratify our worldwide analysis by temporal dimension (short-term and long-term) and by model output (numeric or binary), and discuss management applications. An attempt to perform a meta-analysis based on published models proved limited because of non-equivalence of the metrics and units of the estimators and outcomes across studies, the diversity of models and the lack of information in published works.ca_ES
dc.description.sponsorshipWe acknowledge with gratitude the useful contributions of the three anonymous reviewers and the Associate Editor of this review paper. This research article received a grant for its linguistic revision from the Language Institute of the University of Lleida in 2017.ca_ES
dc.publisherCSIRO Publishingca_ES
dc.relation.isformatofReproducció del document publicat a:
dc.relation.ispartofInternational Journal of Wildland Fire, vol. 26, núm. 12, p. 983-998ca_ES
dc.rightscc-by-nc-nd, (c) IAWF, 2017ca_ES
dc.subjectPredictive modelsca_ES
dc.subjectSpace–time patternsca_ES
dc.titleHuman-caused fire occurrence modelling in perspective: a reviewca_ES

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cc-by-nc-nd, (c) IAWF, 2017
Except where otherwise noted, this item's license is described as cc-by-nc-nd, (c) IAWF, 2017