Abstract

Predicting and estimating forest fire danger is an important part of the system of forest fire prevention and elimination. Geographic information systems (GIS) have instruments for creation, transformation and integration of variables concerned with fire danger. They allow finding geographical and analytical relations to identify areas with high fire incidents probability. Analysis of existing forest fire danger assessment systems showed that they take into consideration such factors of forest fire initiation as anthropogenic load and storm activity. Theoretical estimates and results of experiments prove that there is possibility of forest fire due to action of focused sunlight along with previously mentioned factors. Assessment of forest fire danger caused by focused sunlight is realizable by analysis of forest taxation description of a given forest area. None of the existing systems recognizes this factor. This paper describes geoinformation system that includes toolset for analysis of forest areas taxation aimed at quantitative evaluation of forest fire danger. Radiant heat flux is considered to be reference source of ignition. The system is capable of evaluating probability and classification of forestry quarters by level of fire danger. Performance of algorithm of forest fire danger caused by focused sunlight evaluation in geoinformation system is shown on typical forest area of Timiryazevskoe forestry of Tomsk region. Conceptual basis of GIS system is physically and mathematically proved methodic of forest fire danger assessment. Computational formulae of probability of forest fire initiation are derived from basic statement of probability theory. The system is implemented in specialized software ArcGIS. The system uses standard user interface with additional functionality for assessment of probability of fire incidents in the forest quarters area caused by focused sunlight. Received information is displayed on the map. For extra capabilities in evaluating forest fire danger unique instruments were developed in built-in Python programming language. Probability maps of forest fire initiation in forest quarters were created using proposed model. Application of these maps will be an important component of the forest fire control system.

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