Effect of wind field parallelization on forest fire spread prediction

Forest fire spread prediction is a crucial issue to mitigate forest fire effects. Forest fire propagation models require several input parameters describing the conditions where the fire is taking place. However, some parameters, such as wind, present a different value on each point of the terrain due to topography. So, it is necessary to couple a wind field model that evaluates the wind on each terrain point. However, calculating the wind for each point on large maps is a time consuming task that can make the prediction unfeasible. So, it is necessary to parallelize the wind field computation. One approach is to apply a map partitioning technique, so that the wind field is calculated for each map part. The wind field obtained is lightly different from the one obtained with a single global map, and it is necessary to evaluate the effect of such difference on forest fire spread prediction. © 2014 Springer International Publishing.