A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation

Fire is the main cause of forest destruction in Mediterranean basin countries. Long-term prediction is intended for long-term planning which may serve to characterize and cluster regions as subject to high or low fire risk. This will enable the development of a rational and sensible forest fire prevention and protection policy. The problem with the existing approaches of long-term forest fire risk clustering is that they use crisp sets applying specific cluster boundaries. On the other hand, fuzzy algebra can provide reliable and flexible means of modeling that can be applied by a suitable decision support system. Given a specific area of interest, the evaluation of the long-term forest fire risk can be performed by the use of a triangular and a trapezoidal membership function. The decision support system that has been developed applies an inference mechanism that is based on various aspects of fuzzy sets and fuzzy machine learning techniques. The system has been applied in Greece, but it can be used on a global basis. Results show that the system successfully estimates the forest fire risky areas.