# Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications
## 1 Introduction  
In current and future climate scenarios the resilience and productivity of agricultural systems will be increasingly jeopardized [1]. Furthermore, population growth trends, expected to reach 8.7 billion by 2030 and 9.7 billion by 2050 [2], will further strain food production systems worldwide, which so far have not been able to keep pace [3]. Within this changing context, crops face a threefold obstacle: management-derived challenges as well as increased pressure from abiotic and biotic stressors. Thus, the application of all available advanced technologies towards managing crop variability and maintaining or improving yields and reducing negative impacts on environmental quality, namely advancements in precision agriculture [4], is central to approaching these issues. The possible technological solutions for these issues are multifold within precision agriculture's paradigm. On the one hand, plant breeding and the use of phenotyping technological advances to improve breeding programs [5] allow for obtaining genotypes adapted to various stressors. However, improved management scales are also a central topic to approach. The fundamental functioningof agroecosystems in food production and their role in environmental conservation calls for the development of operational global scale methodologies. In this sense, within the scope of precision agriculture, remote sensing technologies are able to provide crucial contributions to agriculture monitoring [6] and improve our understanding of the impacts of environmental variations [7]. Many of the limitations in the application of remote sensing techniques for precision agriculture of previous years [8] have been overcome with the launches of Sentinel-2 A + B. The Sentinel-2 constellation, with improved spatial, spectral, and temporal resolution was designed specifically to meet the needs of the agricultural community, both farmers and academic researchers with a focus on international agricultural development. Management-derived challenges as well as abiotic and biotic stressors may all be confronted and their negative impacts greatly ameliorated by employing remote sensing technologies to better guide adaptive agricultural management decisions, such as variable rate applications and treatments, which can be assessed and confronted at different levels of precision using different sources of remotely sensed data. Remote sensing data has long been made freely available to help to deploy precision agriculture in crop management to optimize the use of scarce resources but requires the necessary know-how for correct implementation. The combination of imaging and spectroscopy has allowed, for the last five decades since the launch of the NASA (National Aeronautics and Space Administration) Landsat-1 or Earth Resources Technology Satellite (ERTS) and its Multispectral Scanner (MSS) in 1972, the application of satellite-based remote sensing technologies. The use of this technology has played an important role, yet with some limitations, in agriculture monitoring all around the world and will increasingly be needed to assess and confront issues related to global climate change. Remote sensing provides coverage of large areas with high precision and can be a very efficient tool for improved management across scales. In this sense, remote sensing using multispectral images is a proxy for extensive manual crop monitoring operations in the field [9] and provides potential savings in precious time and resources. Precision agriculture has grown and established itself as a central tool in agricultural management to forecast yield, monitor plant stress, and optimize fertilization, irrigation, and soil tilling activities for a more sustainable management of farming practices and improvements in yield for farmers. The launches of Sentinel-2 A + B twin platforms by the European Space Agency (ESA) has resulted in an improvement of precision agriculture possibilities.