The training course aims to deliver the basics related to the acquisition, processing and feature extraction techniques of remotely sensed imageries, paying particular attention to environmental and climate change topics
The remote sensing and Earth observation course for Environmental Engineering aims to provide theoretical knowledge and operational skills relating to the physical assumptions, acquisition systems and processing of data acquired by sensors mounted on board of aerial and satellite platforms. Particular attention will be paid to basic training in the field of multispectral optical remote sensing aimed at generating environmental issues. Particular attention will be paid to free satellite data with medium spatial resolution useful for surveys on a territorial and landscape scale
The main aim is to deliver to student the ability to correctly identify environmental challenges and issues, to better understand possible data to be used, its suitability, and data processing chain in order to extract value added information in a common georeferenced system. Students will be trained in:
- electromagnetic theory, interactions between electromagnetic energy and atmospheric layers and ground surfaces, visual perception and colorimetry
- sensors data acquisition
- image processing
- information extraction
- environmental and climate change related applications.
Related to technical communication:
- ability to analize complex environmental problems, defining proper data to be used, processing chains, information extraction strategies, achieved results publication and dissemination;
- ability to approach different domain of applications using remotely sensed data;
- ability to assess results in a fully quantitative way;
- ability to set up data processing procedures suitable to approach non conventional applications.
Such expertises will be acquired also working directly on application cases drafting also different technical solutions.
At the end of this course the student will have to:
• know the main theoretical assumptions relateci to remote sensing;
• know the main algorithms relateci to the processing of remote sensing data;
• know the main procedures relateci to the use of remote sensing in the various application domain.
At the end of this course the student will know:
• how to describe and correctly interpretate remotely sensed data in digital and cartographic form;
• how to autonomously collect and process remotely sensed data;
• and will have acquired the tools and adequate skills far the interpretation of data and the extraction of information from remotely sensed data.
At the end of this teaching the student will be able to formulate a judgment:
• on the quality of remotely sensed data;
• on information relating to the main aspects of remote sensing.
At the end of the course the student must know:
• How to use a correct and adequate language far the communication of information extracted from remote sensing data.
At the end of this course the student will have:
• the minimum autonomous study skills of remote sensing;
• the ability to autonomously investigate the main aspects of remote sensing.
Students attending this training course, already know geomatics basics (digital mapping, GPS techniques, surveying) and computer science basics.
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Teaching subjects are:
- Remote sensing definition
- Emissivity theory
- Electromagnetic spectra and black bodies
- Electromagnetic source and atmospheric interaction
- Electromagnetic source and ground surfaces interaction
- Visual perception and colorimetry
- Digital images and acquisition systems characteristics
- Data processing algorithms
- Information extraction: digital filters and classifications
- Extracted information assessment
• lntroduction to Remote Sensing: definitions and main physical laws
• Interaction between atmosphere and electromagnetic radiation: atmospheric windows and scattering
• lnteraction between surfaces and electromagnetic radiation: geometrie and physical- chemical charachteristics
• Visual perception and colorimetry basics
• Satellites far Earth Observation: geostationary and sun-synchronous. Main missions, Sensor scheme, digitai image: numerica! definition and operational features (resolutions)
• lmage processing: histogram, contrast enhancement, scatter plots, digitai filters, matrix operators: spectral indices from satellite imagery
• lmage interpretation
• Radiometric pre-processing: radiance/reflectance calibration, dark subtraction
• geometrie preprocessing: image warping
• lmage classification: supervised and unsupervised classifiers
• Classification Accuracy: confusion matrix and statistica! accuracy parameters
The training course is delivered both by theoretical lectures and labs; in the latter, students will use PC to process digital images based on real cases. Every student will access a single PC and will be assisted during all the labs. For the theoretical and labs parts, digital contents will be available since the beginning of the training course and labs will be duplicated based on the number of students attending. Innovative learning will be used, facilitating student’s interaction and organizing a final full day challenge based on the ability to approach a complex environmental issue using open source remotely sensed imageries and mapping data.
The teaching is organized in lessons and operational activities developed with the help of the Envi software. The former are dedicated to the presentation of the theoretical and methodological aspects of the phenomena examined; the latter are aimed at understanding, from an operational point of view, the methods of management, processing and extraction of information from large quantities of data acquired by sensors mounted on board of aerial and satellite platforms.
Specific didactic material will be available, in a digital format, since the beginning of the training course
The following material will be available from the beginning of the lesson:
• manual of the theoretical part of the entire course
• presentation, in PDF format, of each single theoretical lecture
• videolessons of all theoretical lectures (both in ltalian and English)
• videolessons of ali practical laboratory exercises (both in ltalian and English)
• data and materials concerning the carrying out of laboratory exercises
Dispense; Video lezioni tratte da anni precedenti; Materiale multimediale ;
Lecture notes; Video lectures (previous years); Multimedia materials;
Modalità di esame: Prova scritta (in aula); Prova orale facoltativa; Elaborato progettuale individuale; Elaborato progettuale in gruppo;
Exam: Written test; Optional oral exam; Individual project; Group project;
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Evaluation will be based on written and/or oral examinations, both from theoretical and lab parts, and based on the official programme and the lab exercises. Examination could be taken both written and oral; the written examination consists of two different test based on the theoretical and experimental parts. In the first, the candidate should answer to 3 different questions, while in the second, using a PC and a standard software, the candidate will answer to a set of different questions. Results of the examination are then delivered to students by means of didactic portal. Oral examination consists of a set of three questions based on theoretical part and the candidate is then asked to solve, with the usage of a PC and a standard software, a practical exercise.
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: Written test; Optional oral exam; Individual project; Group project;
The exam is aimed at verifying the achievement of sufficient autonomy in tackling an environmental problem using Earth observation data processing techniques useful for extracting added value information.
The theoretical part will be evaluated through a written exam (duration 1.5 hours) in which the student will have to answer at least three questions concerning the different topics proposed during the course. The experimental part will focus on the drafting of a report based on the elaboration of Earth observation data based on a topic and on an area freely chosen by the student.
Students with disabilities or with Specific Learning Disorders (OSA), in addition to reporting via computerized procedure, are also invited to communicate directly to the teacher in charge of the course, with notice of at least one week from the start of the exam session, the compensatory tools agreed with the Special Needs Unit, in order to allow the teacher the most suitable declination with reference to the specific type of exam.
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.