Upon completion of the course, students will acquire the following knowledge: • Survey of agricultural biosystems using geomatics and geophysical methods based on 3D modelling, remote sensing and punctual field measures • Advanced techniques for monitoring and knowing the farming systems • Processing surveyed data by adopting statistical tools and interpreting them through a multidisciplinary approach • Collecting geospatial data and retrieving information from open databases and services (such as the Copernicus program) • Managing, querying and visualising geodata. It is expected that students will acquire the following capabilities: • Design optimal survey methods and integrate data from different measurement techniques and sensors • Process geophysical and geomatic data for agricultural purposes • Develop a multidisciplinary data interpretation method • Render the results with technical reports, thematic maps and digital operable models.

Basic knowledge of the following topics is required: statistics, electromagnetic signals, signal processing, soil science (chemical and physical properties of soil), hydrology, sensors and data acquisition systems, Matlab and Python coding. Course attendance requires fluent spoken and written English, in that all lectures, exercises, and exams will be in English, and communication between students and lecturers is fundamental.

The course consists of two fundamental pillars for monitoring and surveying in agricultural engineering: geophysics (3 CFU) and geomatics (5 CFU). The course has a multidisciplinary approach, where geomatics and geophysics are continuously mixed, stimulating the interdisciplinary analysis capabilities of students and developing “problem-solving” competencies. The geophysics component will focus on geophysical methods that can indirectly measure and map the spatial and temporal variability of soil properties at field scales. Particularly, the methods are suitable for mapping soil types, boundaries, or facies, and identifying contrasting soil components within soil map unit delineations. The best technologies to characterise soil water content and flow patterns and to assess variations in soil texture, as well as other physical and chemical properties (e.g., cations exchange capacity and soil salinity) of interest in agriculture, will be discussed. Finally, methods for determining the depth to subsurface horizons, stratigraphic layers or bedrock will be analysed. The geomatics component will focus on the leading 3D modelling and georeferencing methodologies. First, the GPS and GNSS positioning techniques for localisation, georeferencing of information and autonomous navigation will be analysed, and established procedures for 3D reconstruction with the latest technologies will be presented. LiDAR and drone photogrammetry surveying and processing pipelines will be examined and applied to real case studies (such as yield digitalisation, vegetation growth monitor and biomass estimations). The fundamentals of physical principles of remote sensing and vegetation spectral response will be presented in relation to advanced remote sensing techniques (satellite and proximal) for surveying agricultural fields, mapping, health vegetation index computing, and interpretation. Finally, the GIS platform and tools will be explored for data analysis, visualisation and integration. Where possible, topics will be combined with labs and some external activities, where professional equipment and software will be used.

The course is divided into lectures and laboratory activities, which will alternate, allowing students to experience the concepts acquired during the lectures and use specific machinery and equipment. The course is structured into four macro themes in which geomatic and geophysical interact. The course will consist of 54 hours of lessons and 26 hours of laboratory work. Lectures (54 h) Survey • Overview of the main geomatics tools and methods • Reference systems and digital mapping • Definitions and planning of geomatics survey • GNSS positioning: methodologies and data processing techniques • Principles of photogrammetry and 3D modelling • LiDAR technology and its applications in agriculture • Electromagnetic spectrum and remote sensing • Optical remote sensing from satellite and aerial and terrestrial drones Measuring and monitoring the proprieties of vegetation • Vegetation spectral signature • Multispectral and hyperspectral optical sensor: data format, acquisition, calibration and processing • Vegetation health indices computing (e.g. photosynthetic response, water content, stress conditions) • 3D models for biomass estimation Measuring and monitoring physical proprieties of soil • Design and plan the geophysical monitoring sensors system • Electromagnetic methods for soil mapping and subsoil characterisation • Georadar data acquisition and processing for soil characterisation and soil moisture mapping • Principle and application in agriculture of Time Domain Reflectometry (water content, network of sensors for controlling the irrigation systems) • Data fusion and integration Terrain morphology analysis • Generation of digital terrain models from photogrammetry, LiDAR and GNSS • Terrain analysis through Geographic Information Systems (GIS) algorithms • Geographic Information Systems (GIS) and webGIS: design, data analysis and mapping layout worldwide relevant case studies Laboratory activity (26 h): Multidisciplinary activities will be carried out, involving field data acquisition using geomatics and geophysical equipment to map terrain morphology, soil units, water content, soil salinity, vegetation physics, and geometric properties. Data processing and interpretation using Matlab or open-source codes in Python. Data organisation and interpretation in GIS environment. Depending on the number of students, the class will be divided into two/three groups, and for each activity, each group could be divided into different small groups, according to the organisation that will be communicated during the class. Laboratory work is fundamental to developing the final project.

Educational material will be distributed during the course. All material that is necessary for the course will be presented and discussed in class. Handbook of Agricultural Geophysics (2008) – Edited By Barry Allred, Jeffrey J. Daniels, Mohammad Reza Ehsani - Contents: Agricultural Geophysics Overview. Agricultural Geophysics Measurements and Methods. The Global Positioning System and Geographic Information Systems. Agricultural Geophysics Application Examples. Additional material: Basics of Geomatics (2009) - Mario A. Gomarasca, Springer. Contents: complete overview of existing geomatics techniques.

Exam: Compulsory oral exam; Group essay;

By working in workgroups, a multidisciplinary project will be solved using the theoretical concepts gained during the lectures and summarised in a final report that will be uploaded in the "portale della didattica" one week before the exam. This report will be graded as part of the final score (30%). Each workgroup will also discuss the project and make a final presentation. This presentation will be part of the final score (an additional 20%). If the project's score is positive (report >=18), the student will be admitted to the (mandatory) oral exam, which will be graded separately (an additional 50%). Usually, the oral exam will take about 20-30 minutes, generally based on three questions. The final presentation and oral exam will be done directly in the classroom.

In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.