Vol. 337 No. 1 (2026)
DOI https://doi.org/10.18799/24131830/2026/1/5282
Methodological issues of assessing the fire hazard situation in a forest area using remote sensing data
Relevance. Caused by significant economic, environmental and social consequences after forest fire that substantiate their forecasting, i. e. determining the probability of their occurrence and the dynamics of development. Economic losses are caused by the loss of timber resources, the costs of extinguishing forest fires, etc. Negative social consequences include the loss of life (rescuers, firefighters) and deterioration in the health of residents of settlements in the immediate vicinity of the fire. Forest fires disrupt the ecological balance in nature, reduce biodiversity, and worsen the natural water and gas balance of the environment. In order to take effective operational measures to prevent forest fires and reduce losses from their occurrence, a preventive measure is forecasting by assessing the degree of fire hazard in forested areas. Aim. To develop and test a methodology for assessing the degree of fire hazard in forested areas using satellite and meteorological data. The objects of the study were six areas in the Republic of Sakha (Yakutia), where forest fires occurred in summer 2021: four fire centers and two background areas near the fire sites. Methods. Cartographic, Earth remote sensing, analytical, monographic, descriptive, etc. The work used indices of Nesterov, NDWI, NDMI, NDVI, meteorological data (air and earth surface temperature, their dynamics, precipitation amount). Result. The authors proposed the methodology for assessing the formation of a fire hazard situation in a forest zone using satellite and meteorological data. It is of interest both to employees of scientific organizations engaged in the study of forest fires, and to representatives of the practical sphere (Avialesookhrana, Ministry of Natural Resources, Ministry of Emergency Situations, Roshydromet, Rosleskhoz). In the future, it is possible to improve the proposed methodology by automating the process of collecting and processing meteorological data and indices, using the capabilities of artificial intelligence, and constructing correct mathematical models.
Keywords:
Earth remote sensing, Nesterov index, forest fire, meteorological data, monitoring of fire hazard situation
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