Program components for web-oriented geoinformation system of forest fire danger prediction

The web-oriented geoinformation system for forest fire danger prediction based on a probabilistic fire danger criteria is described in the paper. The new method of the calculation of the probabilistic fire danger criteria is depicted. А new formula for fire danger assessment for a certain time interval of forest fire season is obtained using the basic principles of the probability theory. A definition of the probability using frequency of events is used to calculate fire danger. The statistical data for certain forestry is used to determine all the multipliers in the formula of fire danger. The geoinformation system for forest fire danger assessment based on the method described here is developed by the Django platform in the programming language Python. The system architecture based on Django’s Model-View-Template is described in the paper. The software package that runs on the server allows to get and visualize a set of parameters describing forest fire danger. The GeoDjango framework was used for realization of cartographic functions. A fragment of a forest fire risk map which corresponds to certain value of fire danger is depicted. The estimation of the fire risk and visualization it on the map help to identify areas most prone to fire ignition and spread and to allocate forest fire fighting resources efficiently.