ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011, Vol. 8, No. 1, pp. 118-126

Forest fire occurrence probability assessment: method and approach in Russian remote monitoring information system (ISDM-Rosleskhoz)

A. Podolskaya , D. Ershov , P. Shuliak 
Center for forest ecology and productivity RAS, 117997 Moscow, 84/32 Profsoyuznaya str
The paper is sequential research of fire occurrence probability assessment method developing for the Remote Monitoring Information System (ISDM-Rosleskhoz). Some preliminary results were reported at the previous conferences of Space Research Institute RAS. Deterministic-probability approach of prediction of the wildfire developed in Tomsk State University (Grishin et. al., 2003) is used as a test model to evaluate the probability of forest fires occurrence. According to the model the probabilities a priori of such indicators as the anthropogenic load, the occurrence of fire due to anthropogenic load, the
presence of dry thunderstorms and the forest fire appearance from a lightning discharge are determined by the events frequency. The a priori probabilities of anthropogenic and natural fires based on the long-term data of ground and air observations of forest fire service for the forest protected lands were calculated.
The Grishins deterministic-probability approach uses physical and mathematical models described a time of drying forest fuel layers. Whereas the complexity of the model adjustment at the federal level for different forest vegetation conditions of Russia a time of fuel ignition also assessed via statistical approach. For each weather station a critical weather index was determined for three regional defined periods of fire season (spring, summer, autumn). The daily fire index danger is included in statistical analysis when confirmed by fire availability on that day. The long-term dataset of forest fires and Nesterovs fire danger indices have been used to calculate the critical weather index. The quantitative values of anthropogenic and natural components of the model can be used also for the preliminary assessment of fires origins near weather stations. It is very important for the fires detected by satellite data. The forecast estimates of fires based on our approach and fires registered de facto during last fire period was compared in framework of present paper.
Keywords: forest fires probability, GIS technology, deterministic-probability approach
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