Wildfire threats count analysis by longitudinal models

J.A. Quintanilha and L.L. Ho
Escola Politécnica – Universidade de São Paulo
Av. Prof. Almeida Prado Trav2, n.83
05508-900 São Paulo SP Brazil

The current operational firing monitoring program conducted by IBAMA (Brazil) has collected data of hot spot count, as measurement of wildfire threats, and other explanatory of Amazon region. The aim of this paper is to present the results of statistical analysis of this dataset from 1999 to 2002. From original data, new variables were created. The sample unit was the municipality. The density of hot spot count (the ratio of the hot spot count and the municipality area) was selected as a dependent variable. A longitudinal linear model was used and it identified as relevant explanatory variables: administrative limits, municipalities area, year, rain conditions, legal conditions of the areas, percentage of: deforestation, illegal human occupation, population growth index and agricultural area, as also it pointed out different structures of variance in the dependent variable for different type of the legal conditions of the areas.  From residual analysis, most of standardized residuals (near 90%) are in the interval (-3, +3). However, some neighborhood municipalities must be considered differently since hot spot count are not associated to any of explanatory variables used in this analysis.

Keywords: wildfire threats, hot spot, longitudinal analysis, Amazon region

In: McRoberts, R. et al. (eds).  Proceedings of the joint meeting of The 6th International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15th Annual Conference of The International Environmetrics Society, June 28 – July 1 2004, Portland, Maine, USA.

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