编号 1 (2024)

Natural afforestation of abandoned agricultural lands due to postagrogenic successions leads to changes in the vegetation cover of landscapes in the Central Russian forest-steppe. The article presents a comparative analysis of natural afforestation indicators on abandoned lands, calculated using Landsat OLI, Sentinel-2 MSI and MODIS satellite data. The Sentinel-2-derived indicators are the most informative for assessing the forest cover of abandoned lands. For indicators extracted from Sentinel-2 data, the statistical significance of differences between gradations of forest cover of abandoned lands is highest. The indicators of long-term dynamics of the vegetation index, calculated based on MODIS data, are the most informative for comparing intra-zonal differences in the intensity of abandoned lands afforestation. At the same time, the distribution of abandoned lands by forest cover in the physical-geographical subzones is most pronounced in the histograms of SWIR-reflectance derived from Sentinel-2. Differences in the species composition of forests on abandoned agricultural lands most strongly affect the values of Landsat OLI vegetation index. Its values are more sensitive to differences in the species composition of forests on abandoned lands in comparison with the spectral reflectance.

Features of spatio-temporal variability of the Bering Sea surface temperature were studied by constructing long-term average distributions for different months and using the method of empirical orthogonal functions based on ERA5 reanalysis data based mainly on satellite information, for the period 1998–2020 (spatial resolution of the data is a quarter of a degree, the time interval is one month). In each spatial cell, for each month, the average long-term values of this parameter were calculated, which showed seasonal changes in thermal conditions in the studied water area. Linear trend coefficients have been determined, which showed a stable tendency to warming of the surface layer of sea waters, most pronounced in summer. Extreme deviations from the average long-term values (anomalies) of the surface temperature of the Bering Sea are considered.

This paper presents the results of modeling the risk of forest fires in the west of Nghe An Province (north-central Vietnam) using remote sensing and GIS data. The nine factors influencing the risk of forest fires, including vegetation cover (NDVI vegetation index), surface evapotranspiration, elevation (DEM), slope (slope), aspect, wind speed, ground surface temperature, average monthly precipitation and population density are used to build a forest fire risk mapping model based on machine learning methods, including Random Forest (RF), Suppor Vector Machine (SVM), and Classification and Regression Trees (CART). Various parameters are tested in the RF, SVM, CART algorithms to select the algorithm with the highest accuracy in forest fire risk prediction. The obtained results show that the RF algorithm with the value of the numberOfTrees parameter equal to 100 has the highest accuracy in predicting the risk of forest fires in the study area, expressed through the location of the distribution of forest fire points, as well as the AUC value on the ROC curve. The results obtained in the study can be effectively used for monitoring and early warning of forest fire danger in settlements, helping to reduce damage from forest fires.

Measurement of non-thermal radiation is currently one of the directions of remote sensing of the Earth. Powerful electromagnetic radiation of the atmosphere, initiated by cosmic rays, in the range from low frequencies to the gamma range, has recently been discovered here. Of particular interest is the study of such radiation in the microwave range, where the technique of aerospace research is well developed. This paper presents the results of joint measurements of microwave and gamma radiation of the atmosphere during thunderstorms in the summer of 2022 in Transbaikalia. The aim of the study was to search for relatively long (up to several minutes) electromagnetic radiation near the frequency of 22.2 GHz on the line of the rotational spectrum of water vapor molecules. It was assumed that such a feature could arise due to the appearance of avalanches of escaping electrons generated by cosmic rays. In this process, in addition to the braking gamma radiation, the gas medium is excited, which can cause its superradiance in the microwave range. In the case of strong electrification in fields with a voltage above 0.284 MV/m, a unique phenomenon may occur - a self-sustaining photonuclear reaction in the lower atmosphere in thunderclouds. In this process, the electromagnetic glow can last from units to tens of minutes. In the performed study, several episodes of increasing radiation intensity in the microwave range were detected, accompanied by gamma-ray pulses in a thunderstorm atmosphere. The glow detected in the experiment can be explained by local electrical discharges with increasing electrification of clouds. Another explanation is the occurrence of a self-sustaining photonuclear reaction that creates a large volume of excited gas. The ways of improving the microwave measurement technique for recording high-energy phenomena in the lower atmosphere at a great distance from the measuring equipment, where gamma rays are not recorded, using the satellite are discussed.

The information received from remote sensing satellites for many years has been successfully used in various economic sectors of the Russian Federation. However, there are cases when it is impossible to promptly obtain satellite observations data of the natural and man-made environment state of country various regions (the cloud cover presence of the Earth, the non-passage of spacecraft orbits in a given area at shooting specified time, different spatial resolution of the equipment, etc.). In this case, the space survey customers have a need to obtain subsatellite information products in the form that specific users are dealing with (the state and volume of forest biomass, agricultural, ecological ecosystems, etc. at the shooting time). Therefore, for subsatellite operational observations, it was necessary to create a local monitoring system based on small aircraft: unmanned aerial vehicles with various onboard equipment minimum set (black-and-white and color panoramic cameras, IR radiometers, radars, lasers, etc.) depending on the task.