Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 5, pp. 327-334
Preliminary analysis of forest fires in the Russian Federation in the 2023 fire season based on remote monitoring data
R.V. Kotelnikov
1 , E.A. Loupian
2 , I.V. Balashov
2 1 Center of Forest Pyrology, Branch of the All-Russian Research Institute for Silviculture and Mechanization of Forestry, Krasnoyarsk, Russia
2 Space Research Institute RAS, Moscow, Russia
Accepted: 20.10.2023
DOI: 10.21046/2070-7401-2023-20-5-327-334
Rapid assessment of the results of forest fires during the fire season can be useful for solving various applied problems, including timely assessment of the efforts of forest fire services and planning the work for upcoming fire seasons. The paper presents the first results of assessing fire risk of forests in the 2023 fire season. The work discusses some meteorological features of the season and shows that the 2023 fire season began on average 11 days later than usual. It is noted that in terms of the total area covered by forest fires, the fire season of 2023 cannot be called “extreme”; it should rather be classified as a season of medium or low fire intensity. An attempt is made to use quantitative criteria to assess fire rates in different regions, which would make it possible to compare the situations in regions with different forest conditions. To do this, we analyze the relative fire intensity by region (the ratio of the area covered by fire to the area of forests), which is compared with average data for 11 years, as well as with data from the previous year 2022. A fairly simple criterion is used to classify the situation observed in a particular region, attributing either normal (close to the long-term average), low or high fire rate. For this purpose, we use information on statistical norms obtained for various regions on the basis of information on fire rates for previous years and the observed standard deviations from them. According to the results of the analysis, fire rate was at the long-term average level in 63 % of the country’s territory, whereas it was higher only in 19 % of the territory.
Keywords: forest fires, remote monitoring, relative forest fire intensity
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