Comparison of the Use of Commercial and Open Satellite Data for Precision Agriculture

Purpose. The study focuses on a comparative assessment of the capabilities of open satellite data from the Sentinel missions and high-resolution commercial systems Planet, SkySat, and WorldView in addressing key tasks of precision agriculture. The main objective is to determine the differences in spatial, spectral, radiometric, and temporal informativeness between these types of satellite data, as well as to evaluate the economic feasibility of their use in agricultural production. Special attention is given to practical monitoring scenarios where revisit frequency, level of detail, analytical quality, and integration into digital agro-systems are critically important. Methods. The research applies methods of Earth observation, multispectral analysis, radar interpretation, and geoinformation modelling. The comparison is based on official Sentinel-1 and Sentinel-2 products and commercial imagery from PlanetScope, SkySat, and WorldView. The evaluation was carried out across several groups of criteria: spatial and temporal resolution, spectral composition, radiometric stability, data accessibility, cost, and processing workflow specifics. Data analysis was conducted using SNAP, QGIS, Google Earth Engine, and API tools of commercial providers. Results. The obtained results demonstrate a substantial difference between open and commercial satellite systems in the context of agricultural applications. Sentinel- 2, due to its red-edge and SWIR bands, provides high-quality spectral information essential for vegetation condition assessment, stress detection, and long-term time-series analysis. Sentinel-1 complements optical data with its capability for all-weather monitoring independent of cloud cover. Meanwhile, commercial systems offer significant advantages in spatial resolution and revisit frequency, allowing detection of small-scale anomalies, identification of minor damage hotspots, analysis of crop structure, and timely monitoring during critical periods. Economic assessments indicate that commercial imagery is most cost-effective for high-value crops, intervention-based decision making, or localized tasks requiring enhanced precision, while Sentinel data are optimal for baseline, regular, and large-scale monitoring. A hybrid use strategy is proposed, combining free Sentinel time series with selected high-resolution commercial acquisitions to refine risk areas. Practical significance. The results have substantial applied value for agricultural enterprises, consultants, agronomists, and companies working in the field of precision agriculture. The developed recommendations for selecting satellite data sources enable rational planning of expenditures, optimization of agronomic operations, improved accuracy of zoning maps, timely identification of problem areas, and reduction of economic risks. Integration of different types of satellite data forms a foundation for more adaptive and productive agro-analytical systems, contributing to increased production efficiency, reduced yield losses, and improved resilience to climate-related challenges.