Most forest fires in Korea are spatially concentrated in certain areas and are highly related to human activities. These site-specific characteristics of forest fires are analyzed by spatial regression analysis using the R-module generalized linear mixed model (GLMM), which can consider
spatial autocorrelation. We examined the quantitative effect of topology, human accessibility, and forest cover without and with spatial autocorrelation. Under the assumption that slope, elevation, aspect, population density, distance from road, and forest cover are related to forest fire
occurrence, the explanatory variables of each of these factors were prepared using a Geographic Information System-based process. First, we tried to test the influence of fixed effects on the occurrence of forest fires using a generalized linear model (GLM) with Poisson distribution. In addition,
the overdispersion of the response data was also detected, and variogram analysis was performed using the standardized residuals of GLM. Second, GLMM was applied to consider the obvious residual autocorrelation structure. The fitted models were validated and compared using the multiple correlation
and root mean square error (RMSE). Results showed that slope, elevation, aspect index, population density, and distance from road were significant factors capable of explaining the forest fire occurrence. Positive spatial autocorrelation was estimated up to a distance of 32 km. The kriging
predictions based on GLMM were smoother than those of the GLM. Finally, a forest fire occurrence map was prepared using the results from both models. The fire risk decreases with increasing distance to areas with high population densities, and increasing elevation showed a suppressing effect
on fire occurrence. Both variables are in accordance with the significance tests.
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Document Type: Research Article
Department of Environmental Science and Ecological Engineering,Korea University, Seoul, Republic of Korea
Chair of Ecoinformatics, Biometrics and Forest Growth and Chair of Ecosystem Modelling,Georg-August-University Göttingen, Göttingen, Germany
Department of Disaster Prevention and Safety Engineering,Kangwon National University, Samcheck-si,Gangwon-do, Republic of Korea
Division of Forest Disaster Management,Korea Forest Research Institute, Seoul, Republic of Korea
September 1, 2012
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