Hierarchical space-time models for fire ignition and percentage of land burned by wildfires
Policy responses for local and global fire management as well as international green-gas inventories depend heavily on the proper understanding of the annual fire extend as well as its spatial variation across any given study area. Proper statistical models are important tools in quantifying these fire risks. We propose Bayesian methods to model jointly the probability of ignition and fire sizes in Australia and New Zeland. The data set on which we base our model and results consists of annual observations of several meteorological and topographical explanatory variables, together with the percentage of land burned over a grid with resolution of 1° across Austalia and New Zealand. Our model and conclusions bring improvements on the results reported by Russell-Smith et al. in Int J Wildland Fire, 16:361–377 (2007) based on a similar data set.
KeywordsWildfires Bayesian hierarchical models Spatial statistics
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- Anselin L, Griffith D (1988) Do spatial effects really matter in regression analysis. Pap Reg Sci Assoc 65: 11–34Google Scholar
- Banerjee S, Gelfand A, Finley AO, Sang H (2008) Gaussian predictive process models for large spatial data sets. JRSS B 70: 825–848Google Scholar
- Banerjee S, Carlin B, Gelfand A (2004) Hierarchical modeling and analysis for spatial data. Chapman and Hall, LondonGoogle Scholar
- Breckle SW (2002) Walter’s vegetation of the earth—the ecological systems of the geo-biosphere. Springer, BerlinGoogle Scholar
- Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression. John Wiley, New YorkGoogle Scholar
- Sá ACL, Pereira JMC, Mota B, Charlton M, Fotheringham AS, Barbosa PM (2009) Pyrogeography of sub-Saharan Africa: spatial non-stationarity of fire-environment relationships. J Geogr Syst under reviewGoogle Scholar
- Thomas A, Best N, Lunn D, Arnold R, Spiegelhalter D (2004) GeoBUGS User Manual, version 1.2. http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/geobugs12manual.pdf