Analysis of changes in vegetation indices during the cultivation of agricultural crops

Abstract

Climate change directly affects food security, as it causes more frequent droughts, prolonged periods of heat, uneven rainfall, and extreme weather events, which reduce the yield of major crops and increase the risk of crop loss. An effective solution is the use of digital and space technologies, which enable satellite monitoring of agricultural crops and the resolution of important agronomic issues.
The digital transformation of agricultural production has made satellite data accessible, but its interpretation remains a challenge.
The normalized relative vegetation index is a normalized vegetation index widely used in remote sensing to quantitatively assess vegetation condition based on reflectance in the near-infrared (NIR) and red (RED) parts of the spectrum. NDVI provides a numerical assessment of the degree of photosynthetic activity of plants by evaluating the difference between the absorbed and reflected spectra.
The aim is to quantitatively assess the interannual variability of the NDVI index within a single field, considering the crop grown, the predecessor, the tillage system, and weather conditions.
Methods. The study is based on a systematic approach, within which generally accepted scientific methods of abstract and logical analysis, synthesis, analogy, comparison, and generalization of scientific data in the field of precision farming were used. Scientific works and materials from periodicals in the agricultural field were used to summarize the information.
Results. Data was obtained on the course of technological processes, including data on crop growth, soil moisture monitoring, the presence of pests and warnings about their appearance, as well as yield forecasting.
Traditional methods of land resource management and analysis are quite labor-intensive, and in addition, it is sometimes difficult to provide up-to-date information on various changes in land use. High-resolution multispectral information has been obtained, which makes land use management more costeffective.
The impact of cultivation technology on crop yields plays an indispensable role in managing the growth and development of agricultural crops, and yield forecasting is one of the important fundamental elements of food security. Traditional methods of yield forecasting usually involve rather complex sampling, which not only leads to significant human and material resource costs in practical application, but is also not very effective.
Conclusions. The vegetation index is one of the key tools of modern precision farming. In the conditions of modern Ukraine, with changing climatic conditions, when weather fluctuations significantly affect plant development. The vegetation index is a tool for early diagnosis of problems, the basis of precision farming, a way to reduce risks in arid conditions, and an auxiliary indicator for yield forecasting. In the context of climate change in the forest-steppe zone of Ukraine, its use is not only useful but strategically necessary.