First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Agricultural Sciences and Veterinary Medicine
SUSTAINABLE AGRICULTURE
Course unit
GIS FOR AGRO-ENVIRONMENTAL STUDIES
AVP5073817, A.A. 2017/18

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

Information on the course unit
Degree course Second cycle degree in
SUSTAINABLE AGRICULTURE
AV2293, Degree course structure A.Y. 2016/17, A.Y. 2017/18
N0
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Degree course track SUSTAINABLE AGRICULTURE [001LE]
Number of ECTS credits allocated 4.0
Type of assessment Evaluation
Course unit English denomination GIS FOR AGRO-ENVIRONMENTAL STUDIES
Website of the academic structure http://www.agrariamedicinaveterinaria.unipd.it
Department of reference Department of Agronomy, Food, Natural Resources, Animals and the Environment
E-Learning website https://elearning.unipd.it/scuolaamv/course/view.php?idnumber=2017-AV2293-001LE-2017-AVP5073817-N0
Mandatory attendance No
Language of instruction English
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 is available ONLY for students enrolled in SUSTAINABLE AGRICULTURE

Lecturers
Teacher in charge FRANCESCO PIROTTI AGR/05

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other -- -- 4.0

Mode of delivery (when and how)
Period First semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 4.0 32 68.0 No turn

Calendar
Start of activities 02/10/2017
End of activities 19/01/2018

Examination board
Board From To Members of the board
1 Commissione a.a. 2016/17 01/12/2016 30/11/2017 PIROTTI FRANCESCO (Presidente)
VETTORE ANTONIO (Membro Effettivo)
GUARNIERI ALBERTO (Supplente)

Syllabus
Prerequisites: Knowledge of basic statistics is strongly encouraged (if you know how to correctly use a z-test and a t-test you are ok) and familiarity with basic computer software for data analysis (e.g. MS Excel) is encouraged but not strictly requested.
Target skills and knowledge: Students will learn the models and formats of digital representation of spatial data, the structure of a geographic information system (GIS); they will use an open source GIS software package (QGIS installed from OSGeo) for visual representation of spatial data and analysis of raster and vector data.
The students will acquire knowledge on using GIS tools to interpret spatial data and process multiple layers with environmental variables to extract information, assess and predict dynamics related to the environment.
Examination methods: Final practical exam and evaluation of a project work.

Exam will be practical - using GIS to solve several tasks over data which are provided to the candidate .

The report for the project work is a 4-6 page report on analysis of spatial data using GIS – the type of analysis and data are chosen freelyby the candidate
Assessment criteria: Ability of the candidate to solve problems and analyse spatial data using GIS tools.
The candidate must successfully carry out the tasks requested during the examination and must provide a well-written report of his/her project, with a convincing research question and method to provide answers.
Course unit contents: - spatial data definition, common models of digital representation of spatial data (vector, raster, TIN etc..)
- data source types (file-based, web-based, geodatabases, web services etc…);
- sources of spatial data (satellite images – Sentinels/Landsat, regional and national cartographic data – topographic geodatabases, global datasets – e.g. global forest cover etc…);
- visualizing data, color representations and production of thematic maps from attributes;
- analysis of raster and vector data using GIS tools over single or multiple layers (geospatial relations, raster calculations, interpolation etc...).
Planned learning activities and teaching methods: Lectures will be theoretical and practical at the same time: i.e. “learn by doing” principle. Students will use the data and apply the taught methods using GIS tools provided in the lab.
Proactivity is requested on the project work - students will have to propose their own ideas on how to put to practice the learnt methods over the chosen study area and on data that they mine over the internet.
Seminars will add information on the potential uses of GIS for spatial analysis.
Additional notes about suggested reading: The material used for the course will be made available to students through the Moodle platform of the School at
https://elearning.unipd.it/scuolaamv/login/index.php
Textbooks (and optional supplementary readings)