Corso di Laurea Magistrale in Scienze viticole ed enologiche - SVE

The course will supply fundamentals of multispectral optical remote and digital photogrammetry sensing from satellite/airplane/UAV. In addition, student will be trained in image interpretation and quantitative information extraction from spectral properties of imaged crops. The course introduces students to the most common imaging technics, both ordinary and multispectral, applied in the Precision Farming context. Remote sensing is intended to map crops properties in time and space to derive information useful to support ordinary crop management practices.

Theoretical skills

Students will be given the following theoretical bases:

• Fundamentals of optical multispectral remote sensing
• Fundamentals of aerial digital photogrammetry
• Fundamentals of satellite positioning (GNSS) and digital cartography
• Basics of digital image processing
• Basics of statistical modeling to relate spectral measures from multispectral imagery to agronomic information.

Practical skills

According to the acquired theoretical skills students will be able to:

• select the proper imaging technique and/or dataset to respond to a specific agronomic requirement
• radiometrically and geometrically pre-process imagery to recover measures from raw data
• compute proper spectral indices (NDVI, EVI,SAVI,NDWI etc.) correlated to agronomic properties of crops
• generate and interpret generated  maps  (vigor or other agronomic parameters derived by modeling from spectral indices)
• analyze vigor maps to derive prescription maps
• To process imagery from UAV: flight plan, Ground Control Points survey by GNSS, image bundle adjustment, ortho-mosaic generation, spectral index map generation.

Critical skills

Students will be able to:

• Propose, project and validate the proper solution to respond to a specific agronomic instance (image type selection, survey designing, ground observation sampling, etc.)

Communication skills

Students will be able to:

• properly interact with farmers and with eventual external service suppliers (UAV operators, surveyors, farming machinery experts, etc.) to manage the whole process from ground data through imagery to crop management operations in field (variable rate interventions).

 

Lessons will be given by WEBEX in a Sinchronous Mode by accessing the following link

https://unito.webex.com/meet/enrico.borgogno

All the lessons will be recorded and the correspondent video uploaded onto MOODLE platform within 72 hours.

LE LEZIONI SARANNO ONLINE IN MODALITA' SINCRONA CON COLLEGAMENTO DIRETTO A QUESTO LINK (indirizzo propria pagina webex o altro per docenti delle sedi italiane) E CARICATE ONLINE SU MOODLE ENTRO 72 ORE.

At the beginning of a new lesson students are required to discuss with professor (10 minutes) about the content of the previous lesson. In this context students are invited to answer some technical questions and proposing their own ones.

Exam will be WRITTEN. It includes: a) 4 open questions scoring 5 points each; b) 5 closed questions with the following scores: 1 for correct answer, -0.5 for wrong, 0 for NOT answered; c) on numerical exercise (score = 5) concerning one of the following topics: leveling network adjustment, error propagation, simple and multiple resection, traverse survey, photogrammetric measurements. Total maximum score is 30/30.

 

• Introduction to Remote Sensing: definitions and main physical laws
• Surface and radiation: reflectance, transmittance, absorbance, emittance, roughness.
• Spectral signature of objects;
• Radiation and atmosphere: transmission and scattering. Radiative transfer models.
• The scheme of a generic multispectral sensor: multispectral imagery characteristics
• Satellites for Earth Observation
• Basics of image processing
• Basics of colorimetry           
• Imagery radiometric pre-processing
• Image georeferencing
• Image classification: supervised and unsupervised classifiers; classification validation.
• Spectral Indices: NDVI, EVI, SAVI, NDWI.
• Relating spectral indices to crop features: vigour, productivity, water potential, etc.
• Interpreting maps. Clustering (prescription maps) and estimation (estimate of quantitative agronomic parameters from indices).
• Remote sensing from airplane and UAV
• Basics of digital photogrammetry
• Basics of GNSS
• The UAV data processing workflow: flight plan, Ground Control Points survey by GNSS, image bundle adjustment, ortho-mosaic generation

[1] Computer Processing of Remotely Sensed Images. An introduction (3rd edition), P. Mather, 2006.

[2] Telerilevamento: Informazione Territoriale mediante immagini da satellite,  A. Dermanis, L.Biagi, Casa Editrice Ambrosiana

[3] Basics of Geomatics, M.A. Gomarasca, Springer, 2009.

The methods of carrying out the teaching activity may vary according to the limitations imposed by the current health crisis. In any case, the remote mode is ensured througouth the academic year.