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 intended as a discipline dealing with acquiring, archiving, modelling, analysing, and representing geospatial data. The techniques and tools related to this discipline are devoted to generating value-added information. They can be applied in multiple application areas (e.g., regional and urban planning, natural resources and cultural heritage preservation, climate change, etc.).
As geomatics techniques and tools applicable in various applications, they represent an ideal environment to apply data-driven approaches and develop problem-solving skills in complex cases by integrating other specific competencies.
Consistent with the aims and educational objectives of the master's degree, this course aims to:
• provide knowledge of the fundamental concepts related to geospatial data (e.g. data types and formats, coordinate reference systems, positional precision and accuracy, etc.)
• describe tools and methods for accessing available datasets and assessing their fitness for purpose, mainly by interpreting metadata stored in data catalogues
• understand advanced principles and techniques for the management and analysis of geo-referenced spatial data at different map scales and exploiting complex data structures such as geodatabases
• demonstrate the application of these techniques in different areas through practical examples in various sectors (e.g. transport, landscape planning, environment protection, etc.)
• showcase tools supporting an effective communication of analysis results to different audiences
The above-mentioned educational objectives constitute a set of competencies that can be exploited in different work roles in the planning domain and that will help to cooperate with experts in various disciplines.
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:
• understand the fundamental concept related to geospatial data (knowledge)
• discover existing geospatial datasets and evaluate their suitability concerning the project requirements (skill and expertise)
• use ESRI's geodatabase format and its advanced features (Feature Dataset, Mosaic Dataset, Subtypes, Relationship Class, Network Dataset) (skill)
• analyse remotely sensed images and extract value-added information from them (skill and expertise)
• select complex processes (i.e. geoprocessing workflows, suitability analysis, risk analysis) and argue on their appropriateness (expertise)
• develop communication strategies that include geospatial outputs and that are appropriate to different audiences (skill and expertise)
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 (15 hours):
• list and description of the primary disciplines connected to geomatics
• main types of data (vector, raster) and formats (single files and data containers)
• coordinate reference systems
• the concepts of precision, accuracy, and nominal scale
• main types of cartographic products
• how to discover existing data
ESRI's ArcGIS Suite (9 hours):
• theoretical and practical presentation of the ESRI user interface
• the layer concept and its properties
• geoprocessing: step-by-step processes vs. models
Basics of remote sensing (13.5 hours)
• Introduction to imagery and remote sensing
• Exercises in deriving value-added information from remotely sensed imagery
The geodatabase (9 hours):
• introduction to geodatabases
• the geodatabase, according to ESRI
• Feature Dataset and Network Dataset with analysis examples (e.g. Route, Service Area, Closest facility, OD matrix analysis)
• Relationship Classes and comparison with joins and relates
• Raster Dataset and Mosaic Dataset
• Subtype and Attribute domains
• Attribute domain
Advanced analysis (9 hours)
Best practices in map making (4.5 hours)
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 ;
Modalità 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 disabilità 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'Unità Special Needs, al fine di permettere al/la docente la declinazione più 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 from 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.