Wild fires in BC are likely to increase in intensity and size due to climate change and unprecedented levels of pest infestation. Predicting fire behaviour is complicated due to the large number of factors that control fire ignition and fire spreading. Using various publicly available historical fire, pest, topography, and climate data, this project develops two multiple linear regression (MLR) models to predict natural fire spreading in BC. With careful spatial interpolation and proper transformation of the data, such MLR models can be developed with a good coefficient of determination of 50% ~ 60%. In general, aspect and spring temperatures are the most influential factors of summer fire spreading.

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