PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



Geomatics for Urban and Regional Planning

01GZIYT

A.A. 2026/27

Course Language

Inglese

Degree programme(s)

Master of science-level of the Bologna process in Pianificazione Urbanistica E Territoriale - Torino

Course structure
Teaching Hours
Lezioni 30
Esercitazioni in aula 30
Tutoraggio 20
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Ajmar Andrea   Professore Associato CEAR-04/A 30 30 0 0 4
Co-lectures
Espandi

Context
SSD CFU Activities Area context
ICAR/06 6 B - Caratterizzanti Discipline dell'ingegneria e delle scienze del territorio
2026/27
The course aims to describe the instruments, methods and operating procedures for the use of Geomatics for regional and urban planning, natural resources and climate change domains. Geomatics is intended as a technical and methodological approach able to acquire, archive, model, process and represent georeferenced data suitable for a correct representation and management of environmental issues. Starting with vector and raster data (also available in an open source environment), the course aims to process digital images (mainly acquired by satellite platforms) and mapping data suitable to implement Geographical Information Systems (GIS) at different representation scales.
Geomatics is integrated into this teaching activity as a fundamental technical and methodological approach for the acquisition, archiving, modeling, analysis, and representation of georeferenced data. In the context of the Master’s Degree in Urban and Regional Planning (LM-48), geomatics provides the essential tools for a correct representation and management of spatially-related datasets necessary for informed decision-making. The teaching activity aims to provide students with a broader perspective on how geodata-driven approaches can solve complex planning issues. Consistent with the professional profiles of Urban and Regional planners, Urban Managers, Spatial Analysts, Urban designers, and experts in territorial transformation dynamics, the objectives are to: • Provide foundational knowledge of geospatial data concepts, including coordinate reference systems (CRS), data formats (vector/raster), and positional precision and accuracy; • Develop discovery skills to access available datasets stored in international catalogues and spatial data infrastructures (e.g., INSPIRE, Copernicus), with local to global (e.g. OpenStreetMap) coverage, and assess their "fitness for purpose"; • Master advanced spatial analysis techniques through the use of complex data structures like geodatabases and automated geoprocessing workflows; • Introduce remote sensing as a source for extracting value-added information for territorial monitoring; • Enhance communication skills for effectively sharing analysis results with diverse audiences using modern mapping products and web-based tools like Story Maps. A distinctive feature of this edition is the systematic use of Active Learning methodologies, specifically Team-Based Learning (TBL). This approach is designed to encourage critical thinking, moving beyond the passive acceptance of software outputs to understand the underlying logic and potential biases. Furthermore, the teaching activity integrates soft skills development, focusing on cultural intelligence and the ability to work effectively in permanent, diverse teams.
In this course, the students will learn: • the technological aspects related to remote sensing, digital maps, geodatabses, GIS; • the theoretical aspects related to the use of satellite images to extract thematic and spatial information; • how to access and process available free and open source data; • a critical analysis of the adopted procedures and the related outputs. After completing the course, the students will be able to: • process and extract value added information from satellite images; • process and extract value added information from vector data; • fully design and implement a Geodatabase exploiting a commercial software package (ESRI). The practical exercises involve a personal evaluation of the overall geodatabase design and implementation workflow, with the aim to extract valuable information for regional and urban planning, environmental issues and climate change domains.
At the end of this course, the student will be able to (the level within brackets refers to Bloom's taxonomy): • Remember (Level 1): Recall fundamental geomatics terminology, the main disciplines connected to the field, and the various types and formats of geospatial data (vector and raster); • Understand (Level 2): Explain the conceptual differences between positional precision, accuracy, and nominal map scale, and the core principles of remote sensing systems; • Apply (Level 3): Implement coordinate transformations between different reference systems and utilize international spatial data infrastructures to discover and assess datasets; • Apply (Level 3): Execute geoprocessing workflows and build automated models to process georeferenced spatial data for deriving indicators, such as soil imperviousness ratio; • Analyze (Level 4): Investigate complex territorial relationships by conducting advanced spatial analyses, including network analysis, suitability modeling, and heat risk indexing; • Evaluate (Level 5): Assess and justify the appropriateness of complex geoprocessing results, and critically evaluate the effectiveness and truthfulness of various mapping products through peer review; • Create (Level 6): Design and generate sophisticated communication products, such as Story Maps and professional cartographic layouts, to share analysis results effectively with diverse audiences; • Develop Soft Skills (Affective Domain): Identify personal cultural biases and apply intercultural knowledge frameworks to collaborate effectively and respectfully within diverse, permanent student teams.
Basic concepts about reference systems.
Knowledge of the basic principles of creating, editing, and representing geospatial data would help reach the expected learning outcomes. The course "GIS, Let's (Re-) Start" (01GCOQA) is strongly suggested in case the competencies mentioned above are missing.
Acquisition operational schema Emission laws and external source of energy, Interaction with atmospheric layers Interaction with physical surfaces Density histograms, slicing and scatter plots Basics of colorimetry Digital filtering Unsupervised classifications Supervised classification Confusion matrix Operational satellites and sensors Geometric, radiometric, spectral and temporal resolutions Comprehensive lab devoted to an environmental operational analysis Basics on GIS: Definition of GIS and LIS, the structure of GIS, data types, geometrical data (raster, vector), descriptive data (attributes), descriptor data (metadata), management software tools (commercial and Open Source). A GIS data management software (ArcGIS), some example of geometrical data, attributes, descriptor, layer symbology, thematic mapping, shape files. World Reference system (WRS) for world mapping: movement/deformations of the Earth, static and dynamic WRS, geographic coordinates, cartographic coordinates, cartographic deformations. World reference system (WRS) and cartographic coordinate system in ArcGIS, projection file (prj), world file (.iiw) for raster georeferencing, Coordinate transformation, accuracy of ArcGIS transformation, georeferencing data (raster and vector) with ArcGIS. Digital mapping: definition of digital map, coordinates and coding, nominal scale, level of details, precision/accuracy, kinds of digital map, horizontal/vertical contents Digital mapping: coding system (old, INSPIRE), geometrical and topological structure of map, data file format Data base design: the procedure for DB design, external model, conceptual model (entity-relationships), logical model (relational), physical model, the problem of complex data and multiple data Attributes and DB in ArcGIS, practical exercises assignment for each team DTM/DSM: definition of Digital Terrain Model (DTM) and Digital Surface Model (DSM) dense models, National and International standards, information content, open elevation model (SRDTM) Basic parts of GIS prototypes Spatial geoprocessing: usage of DTM/DSM, interpolation, resampling, surface analysis (slope, aspect, …), basins, 3D spatial analyst in ArcGIS using DTM/DSM for a 3D GIS production Spatial geoprocessing: visibility, sections/profile extraction, buffer, extract, overlay, proximity, statistics Verification of practical exercices for each team Acquisition of georeferenced data: direct survey, fotogrammetry and drone, paper map digitalization, student team of POLITO
Introduction (14 hours): • course introduction; • geomatics fundamentals: basic terminology and related definitions; • GIS data types: vector data, raster data, and various data formats; • coordinate reference systems. ESRI's ArcGIS Suite (3 hours): software sign-in process and navigating projects, ribbons, and panes. Precision, accuracy, and nominal map scale (5 hours). Discovering existing data (7 hours): data catalogues, retrieving OpenStreetMap data, and Copernicus services. Geoprocessing (20 hours): • step-by-step workflows compared with the use of ModelBuilder; • suitability analysis (TBL); • network analysis (TBL); • heat risk index (TBL). Imagery and Remote Sensing (6 hours): image creation, remotely sensed data access, classification (pixel and object-based), and spectral indices. Map making (5 hours): best practices in cartography and the development of Story Maps.
Sustainable development goal 11
The GIS software used in the course is ArcGIS Pro, the latest version. The process for obtaining the software license will be detailed through notices in the teaching portal and during the course’s first lesson. Students are strongly invited to verify in advance if their laptops meet the ArcGIS Pro system requirements listed here: https://pro.arcgis.com/en/pro-app/latest/get-started/arcgis-pro-system-requirements.htm In case of issues, they are invited to inform the teacher promptly.
The course in organized in theoretical classes and laboratories devoted to the usage of specific geomatics software for remote sensing and digital mapping processing.
The course will be delivered as a strongly integrated mix of lessons (30 hours) and related exercises (30 hours), i.e. lessons and exercises will be conducted back-to-back to showcase the application of the theoretical concepts immediately. The lessons will be delivered in a standard classroom equipped with electric sockets. Therefore, Students are invited to bring and use their laptops during the lessons.
The main text consists of the lecture notes provided by the teacher and slides presented during the lessons.
• Mario A. Gomarasca, Basics of Geomatics, Springer, 2014, ISBN: 9781402090141 • Kenneth Field, Cartography, ESRI Press, 2018, ISBN: 9781589484399 • Ghilani, C. D. and P. R. Wolf, Elementary Surveying: An Introduction to Geomatics - Chapter 3, Hall Publishers, 2014 • ArcGIS Pro Help: https://pro.arcgis.com/en/pro-app/latest/help/main/welcome-to-the-arcgis-pro-app-help.htm • Canada Centre for Remote Sensing, Fundamentals of Remote Sensing, https://www.nrcan.gc.ca/sites/www.nrcan.gc.ca/files/earthsciences/pdf/resource/tutor/fundam/pdf/fundamentals_e.pdf • ESA Newcomers Earth Observation Guide, https://business.esa.int/newcomers-earth-observation-guide • MIT GIS Services Group. RES.STR-001 Geographic Information System (GIS) Tutorial. January IAP 2016. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA. • Marc Monmonier, How to lie with maps - 3rd edition, The University of Chicago Press, 2018, ISBN-13: 9780226435923
Slides; Esercizi; Esercizi risolti;
Lecture slides; Exercises; Exercise with solutions ;
Modalita di esame: Prova orale obbligatoria; Prova scritta in aula tramite PC con l'utilizzo della piattaforma di ateneo;
Exam: Compulsory oral exam; Computer-based written test in class using POLITO platform;
... The exam consists of two parts: • The ability to process data thanks to dedicated software, in order to extract added value information. This part is evaluated as vote/30. • Oral/Written examination where is possible to evaluate theoretical aspects acquired during the course. This part is evaluated as vote/30. The final grade is a weighted average of the results of the three previous assessments.
Gli studenti e le studentesse con disabilita o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unita Special Needs, al fine di permettere al/la docente la declinazione piu idonea in riferimento alla specifica tipologia di esame.
Exam: Compulsory oral exam; Computer-based written test in class using POLITO platform;
The assessment of the learning outcomes will be performed in two steps: • a written examination focusing on both knowledge and skills, using closed and open questions and including the usage of specific software adopted in the course, aimed at verifying students' capacity in all topics covered during the classes. The written examination will last 90 minutes, and it will count for 50% of the final grade. No material (except for a pen/pencil) is allowed during the written exam. Only students who obtain a grade equal to or higher than 18/30 are admitted to the oral exam; • an oral examination of all the theoretical aspects covered in the course, aimed at verifying the specific level of knowledge, skills and expertise acquired, the capacity to analyse complex processes and critically discuss analysis alternatives, and the capacity to communicate clearly and unambiguously. The oral examination will last approx. 30 minutes and it will count for 50% of the final grade.
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.
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