Aim. Assess changes in the NDVI of agricultural land in Stavropol Territory under the influence of weather and climate conditions.Methods. Based on earth remote sensing data, the spectral/vegetation index NDVI was calculated. We used data from the Meteor‐M satellite with a spatial resolution of 60 m for the active vegetation period of 2020 (May to September), which made it possible to calculate the NDVI value at different times of the active vegetation period of the main types of agricultural land in the Stavropol Territory. To explain the spatial and temporal variability of NDVI, an analysis of the conditions of heat and moisture supply was carried out using Walter's climatograms at weather stations located in the steppe and semi‐desert landscapes of Stavropol Territory.Results. In 2020, the period of active vegetation in the steppe and semidesert landscapes of Stavropol Territory began in the first ten days of April, when the air temperature rose above +10°С, and ended in mid‐October. In accordance with the change in heat and moisture supply, the NDVI value changed: in general, maximum values were observed in spring and early summer and, as aridity increased, the areas corresponding to low NDVI values increased everywhere. In the steppe zone, where the main crops of winter wheat are located, the NDVI value decreased from 0.45–0.3 at the beginning of the active vegetation period to 0.15 at the end. NDVI values of 0.15–0.30, corresponding to different types of herbaceous vegetation, prevailed at the end of the active vegetation period.Conclusion. The spatial and temporal distribution of the NDVI value over the territory of the Stavropol Territory reflects, first of all, changes in the conditions of heat and moisture supply. The timing of the course of the phenological phases of natural and cultivated vegetation depends on the latter. 2020 was characterized by sufficient moisture at the beginning of active vegetation, as reflected in the high density of seedlings, and, accordingly, a large area of NDVI, corresponding not only to herbaceous, but also to shrubby vegetation within the steppe landscapes. The increase in moisture deficit and harvesting in the second half and end of summer leveled the differences between the steppe and semi‐desert landscapes, since the maximum areas were occupied by territories with NDVI values of 0.15–0.3.
The article presents the possibilities of mapping dynamics of the normalized differential vegetation index (NDVI) onto the territory of the North Caucasian Federal District based on Russian satellite images of medium resolution. In the course of our work, the statistical weather data were processed and analyzed based on the results of long-term ground-based observations at some weather stations. The methods of using remote sensing data for mapping using GIS technologies were explored and NDVI index maps were compiled. Using remote sensing data and the calculated vegetation indices makes it possible to successfully map various processes and phenomena; the maps compiled in this way can be used to solve a wide range of scientific and practical problems.
The article discusses the changes in the NDVI on the territory of the Alexandrovsky and Novoselitsky municipal districts of the Stavropol Territory during the active vegetation period of 2020. The data source were Sentinel-2 thematic images, the spatial resolution of which is 10 m. The schematic maps reflecting the distribution of the NDVI by dates with minimal cloud cover in June-September 2020 have been compiled and analyzed. To explain the spatial and temporal pattern of changes in the areas occupied by different gradations of the NDVI, the data of the Aleksandrovsky weather station for 2020 (the course of temperature and precipitation during the year) were analyzed here as well. The use of remote sensing data and corresponding vegetation indices allows mapping various processes and phenomena in the GIS sphere, and the compiled maps can be used to solve a wide range of theoretical and practical tasks, including crop yields assessement.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.