Development of Information Databases for Vegetation Fire Behavior Prediction ^†

Abstract

To study the vegetation affected by fires and to create databases useful for fire behavior prediction, three methodological approaches are used: (1) selective, (2) standard, and (3) individual-standard. The selective method consists of empirically studying the drying and moistening dynamics of vegetation fuels in terms of fire hazard and burning characteristics in relation to dynamic external factors. This method is used in Russia and Canada. In the standard method approach, all vegetation, forest and non-forest, is divided into pyrological types—“fuel models”. This method is used in the USA. The individual-standard method consists of compiling individual pyrological characteristics of vegetation areas from typical elements that reflect the description of the components of a complex of vegetation fuels, as well as the conditions for their moistening, drying, and burning. This method is being developed in Russia. The essence of the method consists of making an individual pyrological description for any plot of forest and non-forest area with the help of the available descriptions (for example, forest inventory) or aerial satellite images, thus creating an information database useful for the prediction of fire behavior. The method is based on long-term pyrological studies of drying and moistening rates of the primary fire carriers in different regions of Russia. Using the developed software, we will present an example of an information database for predicting the behavior of vegetation fires in the Krasnoyarsk Priangarye, the most fire-prone region of Siberia.