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Geography and Natural Resources

2025 year, number 4

A comprehensive assessment of the fire susceptibility of landscapes in the Tunka depression

A.A. CHERKASHINA, A.V. SILAEV
V.B. Sochava Institute of Geography, Siberian Branch, Russian Academy of Sciences, Irkutsk, Russia
Keywords: fires, landscapes, moisture supply, fire hazard factors, Earth remote sensing data, vegetation indices

Abstract

Based on the integrated use of field, remote and laboratory methods, the fire hazard of landscapes in the Tunka Depression (Southwestern Pribaikalie) has been assessed. The highest frequency of fires is observed in pine forests, confined to sandy massifs in the central part of the depression and the southern slopes. Based on statistical analysis, it has been found that the fire frequency in these forests is, on average, 1,8 times higher compared to forests of other types (small-leaved, cedar, and spruce). In more than half of the cases, fires in pine forests are accompanied by a high degree of damage to the tree stand with the formation of burned wood. Forests with a predominance of small-leaved species are susceptible exclusively to ground fires; their flammability is assessed as the lowest. Among them, the landscapes of the northern slopes are characterized by a complete absence of signs of fires during the study period. Using one-factor dispersion analysis, it has been revealed that with an increase in the NDVI values (improvement of the state of the vegetation cover) and a decrease in the MSI values (increase in the moisture supply of phytocenoses), the fire hazard of landscapes decreases. A linear dependence was found between the granulometric composition, which determines the water-holding capacity of soils, and the level of water stress, as well as the state of vegetation. An increase in fire hazard was noted in sites with a granulometric composition lighter than loam, resulting from a reduced ability of soils to supply sufficient moisture to biotic landscape components. The obtained results confirm the validity of using Earth remote sensing data in general and vegetation indices in particular in studying fire dynamics and assessing potential fire hazard.