SENTINEL-2, HERRAMIENTA EN LA SEGURIDAD AGROALIMENTARIA Y AGRICULTURA DE PRECISIÓN

Background. Food production as the world population increases is an issue of global importance, resulting in uncertainty around agri-food security (AS). It is essential to apply new technology that monitors and makes crop management more efficient to achieve sustainable development (SD). One technology responsible for improving conventional farmers' practices is precision agriculture (PA) using tools such as big data analytics, artificial intelligence and geospatial analysis. In this sense, the monitoring of markers through satellite images requires knowledge for adequate interpretations. Some satellites have multispectral images, monitoring with these has demonstrated high precision in predicting crop yields. There are several satellites, Landsat 8 (L8) and Sentinel-2 (S2) are the most advanced and open access. Objective. To present the spectrophotometric fundamentals and current state of remote sensing with S2 multispectral images in relation to problems facing agriculture. It is concluded that remote sensing is a tool that contributes to the proper management of agricultural production, showing high reliability. Methodology. This review was carried out in accordance with the PRISMA statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses), a systematic analysis of literature in the databases was carried out. MDPI, Springer Link, Science Direct, Taylor and Francis and Google Scholar were consulted. The key words were “Sentinel-2, R2, Salinity, Pest, Nitrogen, Drought”. Zotero (www.zotero.org) was used as a free access bibliography manager; articles that were not related to the research objectives were excluded. Results. Articles related to the objective of this review were identified in the databases; the study was structured based on the needs of precision agriculture (PA). The importance of adequately managing the water demand of crops, salinity stress, pest detection and the movement of nitrogen (N) in the soil-plant-atmosphere interaction. Implications. Remote perception of phenomena at the field level represents an area for improvement in crop management. Increasing resource efficiency is crucial to achieving agri-food security (AS) and thus part of the sustainable development goals (SDGs). Conclusion. The S2 has multispectral images that, when processed, allow obtaining information about the crop, i.e. monitoring stress, humidity in plants and optimization of plant nutrition. With PA, decisions are made for crop management, costs are reduced by reducing losses due to crop stress, and resource efficiency increases.