Geomatics in Agriculture

The course provides the basic knowledge on the methodologies to analyze, describe and model spatial data, in order to produce maps of the soil and vegetation properties. Particularly the course consists of two Teaching Units: T.U. 1 "Analysis of spatial variability in agriculture", T. U. 2 "Remote sensing for agriculture". Through hand-on exercises and presentation of case studies, the T.U. 1 introduces the geostatistical tools necessary for describing the spatial variability and for validating the spatial correlation models; moreover, it introduces the use of softwares to analyse the spatial variability and to create interpolation maps. The T.U. 1 teaches the fundamentals of physical principles of remote sensing and of vegetation spectral signatures; it illustrates the available imageries for land monitoring and their application to support agro-practices; it introduces the up-to-date methodologies in remote sensing to estimate vegetation parameters and the specific data handling in time-series analysis; finally it illustrates the possible use of remote sensed data in precision agriculture practice, through case studies and practical examples carried out with specific software tools.

Knowledge of the fundamental skills to describe, interpret and critically analyze spatial data, in order to produce thematic maps and to assess their accuracy. Ability to use of GIS and software for the analysis and the modeling of spatial data. Basic knowledge on available platforms and relevant features of remote sensing systems. Ability to retrieve remote sensed data taken on agricultural areas, to identify the proper methodologies to get meaningful information to support agro-practices and to exploit them in decision support systems within precision agriculture workflows.