APPLICATION OF EARTH REMOTE SENSING DATA FOR PREDICTING AGRICULTURAL CROP YIELDS

Abstract

Agriculture in the Republic of Kazakhstan plays a strategic role in ensuring the country's food security and exports. This paper shows the effectiveness of remote sensing methods for assessing the productivity of grain crops. In this article, Sentinel-2 space images for the period from 2019 to 2023 are used. Normalized difference vegetation index (NDVI) was used to forecast crop productivity. Space images interpretation and calculation of the NDVI were carried out using ArcGIS software. The article reveals that NDVI values reflect well the biological productivity of agricultural crops during the growing season and show correlation with biomass and yield. The work indicates that the analysis of crop yields will be more accurate if along with NDVI index such indicators of climatic conditions as air temperature and precipitation are used. Forecasting yields is of great practical importance.