Spatio-temporal log-Gaussian Cox processes for modelling wildfire occurrence: the case of Catalonia, 1994–2008
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Scholar |
Otros documentos de la autoría: Serra, Laura; Sáez, Marc; Mateu, Jorge; Varga, Diego; Juan, Pablo; Díaz-Avalos, Carlos; Rue, Håvard
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http://dx.doi.org/10.1007/s10651-013-0267-y |
Metadatos
Título
Spatio-temporal log-Gaussian Cox processes for modelling wildfire occurrence: the case of Catalonia, 1994–2008Autoría
Fecha de publicación
2014Editor
SpringerISSN
1352-8505Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://link.springer.com/article/10.1007/s10651-013-0267-yVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Wildfires have become one of the principal environmental problems in the Mediterranean basin. While fire plays an important role in most terrestrial plant ecosystems, the potential hazard that it represents for human ... [+]
Wildfires have become one of the principal environmental problems in the Mediterranean basin. While fire plays an important role in most terrestrial plant ecosystems, the potential hazard that it represents for human lives and property has led to the application of fire exclusion policies that, in the long term, have caused severe damage, mainly due to the increase of fuel loadings in forested areas, in some forest systems. The lack of an easy solution to forest fire management highlights the importance of preventive tasks. The observed spatio-temporal pattern of wildfire occurrences may be idealized as a realization of some stochastic process. In particular, we may use a space–time point pattern approach for the analysis and inference process. We studied wildfires in Catalonia, a region in the north-east of the Iberian Peninsula, and we analyzed the spatio-temporal patterns produced by those wildfire incidences by considering the influence of covariates on trends in the intensity of wildfire locations. A total of 3,166 wildfires from 1994–2008 have been recorded. We specified spatio-temporal log-Gaussian Cox process models. Models were estimated using Bayesian inference for Gaussian Markov Random Field through the integrated nested Laplace approximation algorithm. The results of our analysis have provided statistical evidence that areas closer to humans have more human induced wildfires, areas farther have more naturally occurring wildfires. We believe the methods presented in this paper may contribute to the prevention and management of those wildfires which are not random in space or time. [-]
Publicado en
Environmental and ecological statistics, 2014, vol. 21, nº 3, p. 531-563Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/restrictedAccess
info:eu-repo/semantics/restrictedAccess
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