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Remote sensing/Applied geophysics
01UCMYN
A.A. 2026/27
Course Language
Inglese
Degree programme(s)
Course structure
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Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
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Co-lectures
Context
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2025/26
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 course Remote Sensing aims to provide students in Environmental Engineering with a solid theoretical and practical foundation in the principles of remote sensing, focusing on the physical fundamentals, data acquisition systems, and processing techniques of remotely sensed data collected from aerial and satellite platforms.
Particular attention is given to the use of multispectral optical remote sensing, especially from freely available satellite data at medium spatial resolution, which is particularly useful for environmental monitoring and analysis at landscape and territorial scales. The course is designed to equip students with key skills for interpreting Earth observation data and applying them to environmental challenges.
An innovative teaching model is adopted: instead of synchronous, in-person software exercises, students will follow an asynchronous learning path supported by video lectures, the ENVI software (made available individually), datasets, and structured activities delivered through Moodle. Students will be able to practice and consolidate their skills at their own pace, with the possibility of repeating modules as needed.
Throughout the course, mentors will provide support both asynchronously and, when required, through live sessions to help students solve technical problems and clarify methodological aspects. After the asynchronous phase, the course will culminate in an intensive specialist seminar dedicated to an advanced application of remote sensing.
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, students will be able to:
Knowledge and understanding
- Demonstrate knowledge of the main theoretical principles underlying remote sensing, including the physical bases of data acquisition from airborne and satellite platforms.
- Understand the fundamental algorithms and methodologies for processing remotely sensed data.
- Recognize and describe the key procedures for applying remote sensing in different environmental domains.
Applying knowledge and understanding
- Describe, interpret, and manage remote sensing data in both digital and cartographic formats.
- Independently acquire and process remotely sensed data using appropriate tools and methods.
- Apply the learned methodologies to extract meaningful environmental information from satellite and aerial imagery.
Making judgements
- Evaluate the quality, reliability, and limitations of remotely sensed data.
- Critically assess the relevance and accuracy of information extracted through remote sensing techniques.
Communication skills
- Use appropriate and technically accurate language to communicate findings and results derived from remote sensing data to both specialist and non-specialist audiences.
Learning skills
- Demonstrate the ability to independently expand their knowledge of remote sensing topics.
- Show initiative in exploring new developments and applications in the field of remote sensing through autonomous study.
Students attending this training course, already know geomatics basics (digital mapping, GPS techniques, surveying) and computer science basics.
Students attending this course are expected to have prior knowledge of the fundamentals of geomatics (including digital mapping, GPS techniques, and surveying) as well as basic computer science skills.
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
The course covers the following main topics:
- Definition and fundamental principles of remote sensing
- Emissivity theory and thermal radiation
- Electromagnetic spectrum and blackbody radiation
- Interaction between electromagnetic radiation and the atmosphere
- Interaction between electromagnetic radiation and terrestrial surfaces
- Human visual perception and colorimetry
- Characteristics of digital images and remote sensing acquisition systems
- Fundamentals of data processing algorithms
- Information extraction techniques, including digital filtering and image classification methods
- Accuracy assessment of extracted information
The course includes theoretical lectures (66%) and practical exercises/laboratory sessions (33%)
“In the academic year 2025/26, the course will be part of the teaching experiment for the implementation of a New Educational Model; students will receive detailed information during the first lesson of the course.”
Practical training activities are organized through an innovative asynchronous learning model. Instead of traditional in-class exercises, students will engage with dedicated Moodle modules that include video tutorials, datasets, and guided workflows for the ENVI software, made available individually to each participant. These modules can be accessed at any time during the year, allowing students to progress at their own pace and repeat the activities as often as needed until certification of competencies is achieved.
Support will be provided by mentors, who will be available both asynchronously (via Moodle) and, when necessary, through live sessions to clarify technical or methodological issues.
Upon successful completion of the Moodle modules, students will be admitted to an intensive specialist seminar held during the final weeks of the course. This seminar, focused on an advanced application of remote sensing, will provide an opportunity to consolidate skills through case-based discussion and hands-on exploration of complex environmental challenges.
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 combines lectures and an innovative asynchronous practical training.
Lectures focus on the theoretical and methodological aspects of remote sensing and Earth observation, including the physical principles, data acquisition systems, and processing techniques.
Practical activities are delivered through Moodle modules, supported by video lessons, datasets, and the ENVI software available to each student. These modules provide hands-on experience in managing, processing, and extracting information from remotely sensed datasets, while offering maximum flexibility in terms of access and repetition. Mentors are available to support students asynchronously and, when needed, through live sessions to address questions and technical issues.
After completion of the asynchronous modules, the course culminates in an intensive specialist seminar dedicated to advanced applications of remote sensing, designed to consolidate the acquired skills and expose students to real-world case studies.
Specific didactic material will be available, in a digital format, since the beginning of the training course
Specific didactic material will be made available in digital format from the beginning of the course. This includes lecture slides, video lessons, datasets, and step-by-step guides for the use of the ENVI software, all accessible through the Moodle platform. Additional reference texts, scientific articles, and freely available satellite data sources will also be suggested to support autonomous learning and further exploration of the topics covered.
Dispense; Video lezioni dell’anno corrente; Materiale multimediale ; Strumenti di auto-valutazione;
Lecture notes; Video lectures (current year); Multimedia materials; Self-assessment tools;
Modalità di esame: Prova orale obbligatoria; Prova pratica di laboratorio; Elaborato progettuale individuale;
Exam: Compulsory oral exam; Practical lab skills test; Individual 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: Compulsory oral exam; Practical lab skills test; Individual project;
Evaluation is based on three complementary components:
Asynchronous Moodle module (30%): Students must complete the digital training modules, including exercises and self-assessment activities, in order to demonstrate proficiency in the use of the ENVI software and in basic data processing workflows. The Moodle module can be attempted multiple times until certification is achieved.
Specialist seminar (20%): After completion of the Moodle module, students are required to actively participate in the final intensive seminar, which focuses on an advanced application of remote sensing. Attendance of at least two-thirds of the total seminar duration is mandatory. The seminar provides the opportunity to apply the acquired methods to real-world case studies and to demonstrate critical and analytical skills.
Oral examination (50%): The final oral exam assesses the student’s knowledge of the theoretical and methodological aspects of remote sensing covered in the lectures, as well as the ability to integrate these with the practical experience gained through the Moodle module and the seminar.
The final grade is expressed in thirtieths. All three components must be successfully completed in order to pass the course.
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.