Assessment of Dependence between the Degree of Fire Impact on Vegetation and the Fire Radiative Power

The article provides the results of analysis of the characteristics of wildfires in various predominant stands of Siberia (50°–75° N, 60°–150° E) based on satellite monitoring data from 2015 to 2021. Thirty-six fires were selected for seven types of different tree stands (vegetation types) with a total area of 19 382 km². Seventy-two images of the Landsat-8 OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) satellite were used in the analysis, as well as data from standard products of MODIS (Moderate Resolution Imaging Spectroradiometer). Based on the processing of remote data (threshold classification of dNBR (differenced normalized burn ratio)) values, statistical patterns of the ratio of disturbance classes for various types of tree stands were revealed. It is shown that, in the case of fires in light coniferous stands, the ratio of disturbance classes is on average 44, 29, and 27% for low, medium and high levels of fire impact, respectively. While this proportion is 63, 14 and 23% in the case of dark coniferous forests, and 59, 26, and 15% in the case of tundra vegetation, respectively. The conjugate analysis of the radiation power of active fire zones using the fire radiative power (FRP) technique demonstrated an increase in the intensity of fires in terms of integral FRP values, proportional to the increase in the degree of fire impact on vegetation. For a representative sample of fires (in various postfire polygons in seven variants of vegetation cover), a significant (R² = 0.77–0.94, p < 0.05) level of correlation was revealed between the values of the normalized burn ratio/differenced normalized burn ratio (NBR/dNBR) and the integral values of the FRP parameter. It has been instrumentally confirmed that high intensity fires (20 000–100 000 MW) are mainly recorded in light coniferous plantations, where the proportion of medium and high degree of fire impact is the greatest (~56%) as well. The results allow us to consider these indices as complementary when solving the problem of estimating the amount of burning biomass, for example, when calculating the volume of direct fire emissions.