Information Systems and Statistics for the Territory
A.Y. 2026/2027
Learning objectives
Module 1: Territorial Information System
The course aims at providing students with advanced knowledge on spatial analysis and the production of thematic cartography in a GIS environment
Module 2: Statistics
The course aims to give students the necessary tools to understand phenomena through statistical analysis of data. Specifically, the student should achieve the following objectives: Knowledge of descriptive and inferential statistics. Evaluation of uncertainty using statistical tests. Correlation analysis between variables and use of linear regression models. Statistical comparison between data sets.
The course aims at providing students with advanced knowledge on spatial analysis and the production of thematic cartography in a GIS environment
Module 2: Statistics
The course aims to give students the necessary tools to understand phenomena through statistical analysis of data. Specifically, the student should achieve the following objectives: Knowledge of descriptive and inferential statistics. Evaluation of uncertainty using statistical tests. Correlation analysis between variables and use of linear regression models. Statistical comparison between data sets.
Expected learning outcomes
Module 1: Territorial Information System
The course aims at providing an advanced understanding of GIS by showing their utility in practical environmental and territorial applications; it also aims at providing students with the necessary ability to solve spatial problems.
At the end of the course, students must demonstrate to have acquired the following competences:
- understand characteristics of spatial data, including Digital Elevation Models and orthophotos;
- to understand and discriminate between the different reference systems in which these data are expressed
- to be able to associate raster and vector data to the appropriate reference system and/or cartographic representation;
- to be able to import, export and convert data in raster and vector format between different reference systems and cartographic projections;
- to understand the characteristics of vector and raster structures and the information necessary to georeference them
- to understand spatial interpolation techniques for the production of raster data (DEM and orthophotos); -
- to be able to carry out queries and spatial selection on vector data and attributes;
- to be able to use the raster calculator to select and analyse raster data
- to understand and successfully apply georeferencing techniques on raster data;
- to be able to break down problems into the steps required to solve it, identifying the most appropriate GIS tools for each case.
Module 2: statistics
Describe the phenomena by the main statistical indicators; Plan a sample surveys; Use the methodology of the analysis of variance at 1 factor; understand the results of statistical surveys.
The course aims at providing an advanced understanding of GIS by showing their utility in practical environmental and territorial applications; it also aims at providing students with the necessary ability to solve spatial problems.
At the end of the course, students must demonstrate to have acquired the following competences:
- understand characteristics of spatial data, including Digital Elevation Models and orthophotos;
- to understand and discriminate between the different reference systems in which these data are expressed
- to be able to associate raster and vector data to the appropriate reference system and/or cartographic representation;
- to be able to import, export and convert data in raster and vector format between different reference systems and cartographic projections;
- to understand the characteristics of vector and raster structures and the information necessary to georeference them
- to understand spatial interpolation techniques for the production of raster data (DEM and orthophotos); -
- to be able to carry out queries and spatial selection on vector data and attributes;
- to be able to use the raster calculator to select and analyse raster data
- to understand and successfully apply georeferencing techniques on raster data;
- to be able to break down problems into the steps required to solve it, identifying the most appropriate GIS tools for each case.
Module 2: statistics
Describe the phenomena by the main statistical indicators; Plan a sample surveys; Use the methodology of the analysis of variance at 1 factor; understand the results of statistical surveys.
Lesson period: First year
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First year
Prerequisites for admission
STATISTICS:
The students should be familiar with basic concepts of Mathematics (crash courses available).
TERRITORIAL INFORMATION SYSTEMS:
It is useful although not required to have followed a basic GIS course; basic knowledge of cartography and reference systems are also useful; it is necessary to possess basic IT skills.
The students should be familiar with basic concepts of Mathematics (crash courses available).
TERRITORIAL INFORMATION SYSTEMS:
It is useful although not required to have followed a basic GIS course; basic knowledge of cartography and reference systems are also useful; it is necessary to possess basic IT skills.
Assessment methods and Criteria
STATISTICS
Exam with multiple-choice questions and exercises to be completed on a computer.
GEOGRAPHIC INFORMATION SYSTEMS:
The exam will be conducted orally through the presentation of a project demonstrating the acquisition of skills in data processing, visualization, and querying using QGIS, followed by theoretical questions on the course contents.
To pass the exam, the student must demonstrate, both during the oral discussion and in the practical component, the knowledge and skills listed in the learning objectives.
In the grading process, the project presentation accounts for approximately 60% and assesses the ability to apply knowledge as well as independent learning skills. The answers to the oral questions, which account for the remaining 40%, assess the theoretical and methodological knowledge base.
Students with certified specific learning disorders (SLD) must agree on compensatory measures with the instructor, in accordance with the university guidelines.
There is no distinction between attending and non-attending students as regards the mode of assessment.
Exam with multiple-choice questions and exercises to be completed on a computer.
GEOGRAPHIC INFORMATION SYSTEMS:
The exam will be conducted orally through the presentation of a project demonstrating the acquisition of skills in data processing, visualization, and querying using QGIS, followed by theoretical questions on the course contents.
To pass the exam, the student must demonstrate, both during the oral discussion and in the practical component, the knowledge and skills listed in the learning objectives.
In the grading process, the project presentation accounts for approximately 60% and assesses the ability to apply knowledge as well as independent learning skills. The answers to the oral questions, which account for the remaining 40%, assess the theoretical and methodological knowledge base.
Students with certified specific learning disorders (SLD) must agree on compensatory measures with the instructor, in accordance with the university guidelines.
There is no distinction between attending and non-attending students as regards the mode of assessment.
Territorial Information System
Course syllabus
Recalls of basic cartographic concepts: reference systems, projections, contents of maps; Italian official cartography.
Geographic information systems: definition of conceptual and logical models.
Recalls of basic GIS concepts:
Raster data: Spatial and radiometric resolution. Georeferencing raster data. Analysis of raster data. Most common raster formats;
Vector data: primitives, entities; topological primitives. Most common vector formats.
Vectorization and cartographic editing.
Visualization, selection and query of raster and vector attributes.
Techniques and technologies to acquire data for the generation of Digital Elevation Models, orthophotos, and GIS at large.
Digital Elevation models (DEM). DEM components. Interpolation models and data structures.
DEM operations.
Digital orthophotos. Advantages and disadvantages compared to numerical cartography. Generation of orthophotos.
Databases at municipality, regional and national level, techniques for data distribution and sharing (webGIS, geoservices).
Lab workshops.
Use of DEM generation software, multi-temporal comparisons, volume calculations.
Presentation and use of QGIS: data import, definition of the reference system, data export, operations on the geometry and attributes of vector data.
Queries, join and spatial selection. Zonal statistics.
Georeferencing raster data. Using the raster calculator.
DEM operations.
Applications of vector and raster data for spatial analysis.
Geographic information systems: definition of conceptual and logical models.
Recalls of basic GIS concepts:
Raster data: Spatial and radiometric resolution. Georeferencing raster data. Analysis of raster data. Most common raster formats;
Vector data: primitives, entities; topological primitives. Most common vector formats.
Vectorization and cartographic editing.
Visualization, selection and query of raster and vector attributes.
Techniques and technologies to acquire data for the generation of Digital Elevation Models, orthophotos, and GIS at large.
Digital Elevation models (DEM). DEM components. Interpolation models and data structures.
DEM operations.
Digital orthophotos. Advantages and disadvantages compared to numerical cartography. Generation of orthophotos.
Databases at municipality, regional and national level, techniques for data distribution and sharing (webGIS, geoservices).
Lab workshops.
Use of DEM generation software, multi-temporal comparisons, volume calculations.
Presentation and use of QGIS: data import, definition of the reference system, data export, operations on the geometry and attributes of vector data.
Queries, join and spatial selection. Zonal statistics.
Georeferencing raster data. Using the raster calculator.
DEM operations.
Applications of vector and raster data for spatial analysis.
Teaching methods
The course includes frontal lectures on theoretical subjects and laboratory exercises using QGIS (for data processing in a GIS environment) and other tools for DEM analysis. The proportion of frontal lectures and laboratory exercises is 2:3.
Teaching Resources
The reference text for the course is: F. Migliaccio, D. Carrion. Sistemi informativi territoriali. UTET, 2016.
Suggested readings will be provided during classes.
Lecture presentations will be made available through the Ariel website.
Suggested readings will be provided during classes.
Lecture presentations will be made available through the Ariel website.
Statistics
Course syllabus
1) Sampling from populations and statistical variables.
2) Frequency distributions, histograms, barplots.
3) Location (average, mode, median) and dispersion (range,standard deviation, variance) indices, quantiles. Outliers.
4) Sample space, events, probability.
5) Discrete and continuous random variables.
6) Confidence intervals.
7) Simple linear regression.
8) Case studies.
The programme and examination procedures are the same for both attending and non-attending students.
2) Frequency distributions, histograms, barplots.
3) Location (average, mode, median) and dispersion (range,standard deviation, variance) indices, quantiles. Outliers.
4) Sample space, events, probability.
5) Discrete and continuous random variables.
6) Confidence intervals.
7) Simple linear regression.
8) Case studies.
The programme and examination procedures are the same for both attending and non-attending students.
Teaching methods
Lectures and classroom practice.
Teaching Resources
1) "Introduzione alla Statistica", di M. K. Pelosi e T. M. Sandifer, ed. McGraw-Hill, 2009.
3) Notes/slides downloadable from MyAriel - UNIMI site.
3) Notes/slides downloadable from MyAriel - UNIMI site.
Modules or teaching units
Statistics
CEAR-04/A - Geomatics - University credits: 6
Exercises: 24 hours
Lessons: 32 hours
Lessons: 32 hours
Professors:
Baldi Lucia, D'Alessandro Felice
Territorial Information System
CEAR-04/A - Geomatics - University credits: 6
Lessons: 48 hours
Professor:
Fugazza Davide
Professor(s)
Reception:
on appointment
Via Celoria 2, Milan, Italy, 3rd floor (or by Skype/Teams/Zoom)