Comparative Analysis of Vegetation Indices on Agricultural Images of Different Modalities

Abstract

Remote sensing is becoming an increasingly in-demand tool in agriculture, allowing for effective monitoring of crop conditions and informed agricultural decision-making. This paper presents a comparative analysis of vegetation indices (NDVI, EVI, SAVI, and NDMI) calculated using data from an unmanned aerial vehicle (UAV) and the Sentinel-2 L2A satellite, with an agricultural field in the Stavropol Region serving as an example. The work demonstrates that UAV data provides high detail and enables the identification of local stress zones, while Sentinel-2 satellite images offer regular monitoring and facilitate the tracking of crop growth dynamics. The combined use of these data sources enhances the accuracy of vegetation condition assessments and can help optimize precision farming technologies.