Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0
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AuthorMartos Núñez, María Vanesa; Ahmad, Ali; Cartujo Cassinello, Pedro; Ordóñez García, Bonifacio Javier
Agriculture 5.0DronesRemotely piloted aircrafts (RPAs)Precision agricultureRemote sensingInternet of Things (IoT)Digital agricultureSustainable Development GoalsSensorsAgricultural robots
Martos, V... [et al.]. Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0. Appl. Sci. 2021, 11, 5911. [https://doi.org/10.3390/app11135911]
SponsorshipEuropean Commission 101007702 872181; Junta de Andalucia P18-H0-4700
Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.
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