Abstract
Nowadays, cost-optimization of aerial patrolling plays a key role in the context of limited aerial forest protection funding. Forest Fire Danger Class is the main indicator that regulates the work of forest fire services. Usually, it’s calculated by the nearest weather station data. Some information systems use the mean of several nearby weather stations to estimate large areas, such as the surveyed area of aerial forest protection. The idea of using the mean weighted index with the weather stations weighting factor is not new. Even though, this idea isn’t widespread due to the calculation complexity and questionable efficiency in practice, this study proposes a scientifically substantiated method of quantitative comparison of two approaches and the direct calculation method of the economic impact when transition to using the mean weighted Forest Fire Danger Class calculation algorithm. The first time such an indicator was used to obtain derivatives of analytical information products. A long-term analysis of forest fire rate showed that the weighted mean of the Forest Fire Danger Class value is 6.7% greater in correlation with the number of forest fires than the usual mean value. The use logarithmic transformation of the forest fire occurrence frequency and population density allows statistical criteria to be reasonably used.
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