Valuing Weather Observation Systems For Forest Fire Management

Weather information is an integral part of modern fire management systems. In this paper, we investigate, by means of simulation studies, how improvements in the weather observation systems help to reduce burned area by targeting and monitoring places ripe fires are likely to occur. In our model, the air patrolling schedule is determined by the Nesterov index, which is calculated from observed weather data. We use two weather data sets based on ldquoroughrdquo and ldquofinerdquo grids. The reduction of the total burned area, associated with an air patrolling schedule based on the ldquofinerdquo grid, indicates the benefits of using better weather observations. We, also, consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. Finally, we investigate the system of systems effect. We find the largest marginal improvement from the rough grid results when we increase the quality of observations in most critical areas.