A heuristic expert system for forest fire guidance in Greece

J Environ Manage. 2002 Jul;65(3):327-36. doi: 10.1006/jema.2002.0592.

Abstract

Forests and forestlands are common inheritance for all Greeks and a piece of the national wealth that must be handed over to the next generations in the best possible condition. After 1974, Greece faces a severe forest fire problem and forest fire forecasting is the process that will enable the Greek ministry of Agriculture to reduce the destruction. This paper describes the basic design principles of an Expert System that performs forest fire forecasting (for the following fire season) and classification of the prefectures of Greece into forest fire risk zones. The Expert system handles uncertainty and uses heuristics in order to produce scenarios based on the presence or absence of various qualitative factors. The initial research focused on the construction of a mathematical model which attempted to describe the annual number of forest fires and burnt area in Greece based on historical data. However this has proven to be impossible using regression analysis and time series. A closer analysis of the fire data revealed that two qualitative factors dramatically affect the number of forest fires and the hectares of burnt areas annually. The first is political stability and national elections and the other is drought cycles. Heuristics were constructed that use political stability and drought cycles, to provide forest fire guidance. Fuzzy logic was applied to produce a fuzzy expected interval for each prefecture of Greece. A fuzzy expected interval is a narrow interval of values that best describes the situation in the country or a part of the country for a certain time period. A successful classification of the prefectures of Greece in forest fire risk zones was done by the system, by comparing the fuzzy expected intervals to each other. The system was tested for the years 1994 and 1995. The testing has clearly shown that the system can predict accurately, the number of forest fires for each prefecture for the following year. The average accuracy was as high as 85.25% for 1995 and 80.89% for 1994. This makes the Expert System a very important tool for forest fire prevention planning.

MeSH terms

  • Conservation of Natural Resources*
  • Disaster Planning
  • Environment
  • Fires*
  • Forecasting
  • Fuzzy Logic
  • Greece
  • Humans
  • Policy Making
  • Politics*
  • Social Conditions
  • Trees*