First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Agricultural Sciences and Veterinary Medicine
FORESTRY AND ENVIRONMENTAL SCIENCE
Course unit
REMOTE SENSING AND INFORMATION SYSTEMS
AGO2045052, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
FORESTRY AND ENVIRONMENTAL SCIENCE
AG0062, Degree course structure A.Y. 2017/18, A.Y. 2018/19
N0
bring this page
with you
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination REMOTE SENSING AND INFORMATION SYSTEMS
Website of the academic structure http://www.agrariamedicinaveterinaria.unipd.it/
Department of reference Department of Land, Environment, Agriculture and Forestry
E-Learning website https://elearning.unipd.it/scuolaamv/course/view.php?idnumber=2018-AG0062-000ZZ-2017-AGO2045052-N0
Mandatory attendance No
Language of instruction Italian
Branch LEGNARO (PD)
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge FRANCESCO PIROTTI ICAR/06

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses AGR/05 Forestry and Silviculture 6.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Practice 3.0 24 51.0 No turn
Lecture 3.0 24 51.0 No turn

Calendar
Start of activities 01/10/2018
End of activities 18/01/2019
Show course schedule 2019/20 Reg.2017 course timetable

Examination board
Board From To Members of the board
7 Commissione a.a. 2018/19 01/12/2018 30/11/2019 PIROTTI FRANCESCO (Presidente)
VETTORE ANTONIO (Membro Effettivo)
GUARNIERI ALBERTO (Supplente)
LINGUA EMANUELE (Supplente)
6 Commissione a.a. 2017/18 01/12/2017 30/11/2018 PIROTTI FRANCESCO (Presidente)
VETTORE ANTONIO (Membro Effettivo)
GUARNIERI ALBERTO (Supplente)
LINGUA EMANUELE (Supplente)

Syllabus
Prerequisites: The course requires basic knowledge on the principles of physics (optical) of mathematics and of applied statistics. It is an added value if the student knows how to use basic computer software (spreadsheets), better if related to viewing/editing digital images.
Target skills and knowledge: Understand principles of electro-magnetic energy (EEM) and how it is converted to a digital image representation in its dfferent formats.
Acquire skills on defining procedures to apply to digital images for the following objectives:
- get image characteristics;
- use color scales and different band combinations to enhance visualization;
- visualization optimization methods - scale stretching and histogram equalization;
- radiometric calibration and atmospheric correction;
- geometric correction
- using indices to study environmental phenomena - e.g. the NDVI index for estimating vegetation stress;
- automatic and semi-automatic segmentation methods, supervised and unsupervised

The course participants will also be taught where to find available data sources of image data and how to deal with a correct cartographic reference system and format.

Students will learn how to use a dedicated geographic information system software to process remte sensing data products and other information layers derived from multiple sources.
Examination methods: Verification of apprehension of the course topics will be carried out with the following:
1. A multiple choice exam on theory (20%)
2. A practical exam, the candidate will have to solve tasks regarding analysis of digital images from remote sensing. (30%)
3. Final project where the candidate will propose his/her remote sensing application and provide his/her own data. (50%)
Assessment criteria: 1. Multiple choice exam on theory (20%)
2. A practical exam, the candidate will have to solve tasks regarding analysis of digital images from remote sensing. (30%)
3. Final project where the candidate will propose his/her remote sensing application and provide his/her own data. (50%)
Course unit contents: Introduction to the physical principles of the behaviour of light.
How sensors work, how the light is recorded into digital information.
Digital images: formats, principles of data storage.
Procedures to apply to digital images for the following objectives:
- visualization using different color scales
- optimization methods
- radiometric calibration and atmospheric correction
- geometric correction
- moving window filters
- automatic and semi-automatic classification methods, supervised and unsupervised
- validation techniques and accuracy metrics, using confusion matrices and derived indices

Post-processing of processing results from digital image analysis for cartographic representations.
Sensors available and data sources; how to evaluate effective potential for a project.
Introduction to advanced programming tools using Google Earth Engine - application potentials.
Planned learning activities and teaching methods: Lectures: 24 hours
Labs: 24 hours
Article reading
Writing a report on the article
Preparation of a presentation on the article
Writing a report on the "lab project"
Additional notes about suggested reading: - Lecture notes and handouts which will be accessible at the following link: https://elearning.unipd.it/scuolaamv/

Students can ask for an appointment to meet at anytime via email.
Textbooks (and optional supplementary readings)
  • P.A. Brivio, G.M. Lechi, E. Zilioli, Principi e metodi di Telerilevamento. Grugliasco (TO): CittàStudi Edizioni, 2006. Cerca nel catalogo
  • Lillesand T., Kiefer R.W., Chipman J., Remote Sensing and Image Interpretation. --: --, --. Cerca nel catalogo
  • Mario A. Gomarasca, Elementi di Geomatica. --: --, 2004. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

Sustainable Development Goals (SDGs)
Climate Action Life Below Water