# Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0
## 1 Introduction  
Constant industrial innovation has made it possible that 2021 has been officially marked by the European Commission as the beginning of the era of \"Industry 5.0\" [1]. The industrial world, including the agricultural sector, is starting this year by getting a bit closer to digitalized and automated systems. Although, agriculture began in the Copper Age, after the Neolithic period, when man started cultivation by making use of wooden instruments and domesticating animals, this was then revolutionized through the use of metallic equipment for crop cultivation and this time was categorized as the firstand second agricultural revolutions. The third and fourth industrial revolutions brought robotics, machines, telecommunication systems, genetic decoding, etc., to agriculture. The fifth and current revolution is based on artificial intelligence (AI) and cloud computing, applied to agricultural remote sensing (RS). A simple illustration of all the principal industrial revolutions, with respect to agriculture, is presented in Figure 1.  
Figure 1: An illustration of industrial revolutions, with respect to agriculture, over time. Representative events/technologies are mentioned in each respective technological era, although they are not limited to only these. The increasing world population, climate change, and sustainable development goals require the agriculture sector to be efficient and sustainable: thereby ensuring food safety and security. According to the Food and Agriculture Organization (FAO), current agricultural production must increase by 70 % by 2050 considering the increasing demand for high quality and environmentally friendly food [2]. Similarly, on 25 September, 2015, the United Nations (UN) general assembly approved the agenda \"Transforming our world: the 2030 Agenda for Sustainable Development\", which is an action plan for the prosperity of people and the planet [3]. Under this agenda, 17 Sustainable Development Goals (SDGs) were embodied, replacing the previously established Millennium Development Goals (MDGs), with a timeframe of completion from 2015 to 2030. Out of these 17 SDGs, the second SDG is \"zero hunger\", i.e., eradicating the hunger, as it was estimated that, in 2015, around 690 million people were suffering from hunger [3,4]. This situation has worsened with the COVID-19 pandemic by affecting food transport systems and threatening people's access to food due to the associated loss of income or increased food prices. In this context, FAO considers that agriculture can contribute to achieving the SDGs, particularly SDG-2, by providing healthy food that is directly related to better health and a productive life. The aims of SDG-2, to eliminate hunger and ensure access for all people, particularly the poor and in vulnerable situations, including infants, to healthy, nutritious, and sufficient food all year round (goal 2.1: SDG-2), are very ambitious. Nevertheless, agriculture has the potential to fulfil these objectives by enhancing the income of small-scale farmers (goal 2.2: SDG-2), strengthening the capacity to combat climate change, extreme weather events (e.g., droughts, fires, floods and other disasters), and progressively improving soil and land quality (goal 2.4: SDG-2). However, in order to do all of the above, a change is required in the way in which all stakeholders in the agri-food ecosystem approach the production process. The first and perhaps the most important step towards this goal is to change the way decisions are made at all levels of agricultural production, from the most primary level of the farmer who is called upon to make decisions every day on his cultivation to the agronomists and decision makers in large agri-food enterprises. Storage and analyses of large volumes of data (big data) for predictions (e.g., production or spread of diseases) but also for the possibility for agri-food companies to produce, from the data collected by digitization of production, information that is relevant to the value of their products and services.