GIS, Remote Sensing, and Forecasting Systems for Precision Agriculture Development

Precision Agriculture (PA) primarily aims to maximize productivity while reducing impacts on the environment. This is made possible thanks to the implementation of advanced land monitoring technologies, such as GIS (Geographic Information Systems), together with other data generators in all phases of agricultural operations, from cultivation to storage. With the aim of contributing to the evolution of this field of research, this article describes an integrated system capable of managing information on climatic variables coming from an innovative and experimental atmospheric simulator and on parameters indicating the state of vegetation obtained through Remote Sensing and UAV techniques. All this to collect all the necessary information in a GIS implemented for the automation of an agricultural vehicle and a drone equipped for fertilization. The innovation of the present research consists precisely in the atmospheric simulator which, exploiting the SPH model (Smooth Particles Hydrodynamic) for the interaction of the atmosphere particles, taking as input the DEM (Digital Elevation Model) of the area under study and the historical data of meteorological stations contained in it, returns as output a punctual distribution of some atmospheric variables fundamental for precision agriculture, such as rain and wind from which the three-dimensional trend can be obtained. These parameters, together with in loco sensors' data, are therefore fundamental for planning the action of both agricultural vehicles and drones and for making the production process more efficient. The operation of this system was tested on an area in the province of Reggio Calabria.