Corso di Laurea Magistrale Interateneo in Geografia e Scienze Territoriali (LM-80)

No requirement is strictly due for this module, but basics of Mathematics, Physics, Statistics, GIS and Survey (GNSS, ordinary and digital photogrammetry) are appreciated.

Fundamentals of multispectral optical remote sensing aimed at the generation thematic maps in the environmental domain. The focus  is on the free available image datasets having a middle geometric resolution, useful for investigations at the territorial and landscape scale.

Knowledge and understanding
At the end of this course the student will have to:
- know the main theoretical assumptions related to remote sensing;
- know the main algorithms related to the processing of remote sensing data;
- know the main procedures related to the use of remote sensing in the various application domains.

Applying knowledge and understanding
At the end of this course the student will know:
- describe and correctly interpretate remotely sensed data in numerical and cartographic form.
- autonomously collect and process remotely sensed data.
- have acquired the tools and adequate skills for the interpretation of data and the extraction of information from remotely sensed data.

Independent judgement
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.

Communication skills
At the end of the course the student must know:
- use a correct and adequate language for the communication of information extracted from remote sensing data.

Learning skills
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.

• Introduction to Remote Sensing: definitions and main physical laws
• interaction between atmosphere and electromagnetic radiation: atmospheric windows and scattering
• Interaction between surfaces and electromagnetic radiation: geometric and  physical- chemical charachteristics  
• Visual perception and colorimetry basics                                                                                  
• Satellites for Earth Observation: geostationary and sun-synchronous. Main missions, Sensor scheme, digital image: numerical definition and operational features (resolutions)                                                        
• Image processing: histogram, contrast enhancement, scatter plots, digital filters, matrix operators: spectral indices from satellite imagery                                                                                                                     
• Image interpretation         
• Radiometric pre-processing: radiance/reflectance calibration, dark subtraction      
• geometric preprocessing: image warping                                                                                                             
• Image classification: supervised and unsupervised classifiers
• Classification Accuracy: confusion matrix and statistical accuracy parameters

The module is made of lectures (40 hours) where theoretical aspects are coupled with practical examples (laboratories, 14 hours) concerning operational processing of satellite data. Students are trained on the basic use of specific processing software (ENVI) useful for the extraction of territorial information from satellite data. Students will be provided with slides and data that the teacher uses during lessons  through the CAMPUSNET system.

The exam will consist of two parts:

1. Oral examination on theoretical topics

   • Discussion of the topics covered during the course, with a particular focus on the fundamentals of remote sensing, satellite sensors and platforms, image processing methods, and environmental applications of open-source satellite data.

2. Submission and discussion of a written report

   • Development of an environmental analysis based on open-source satellite data, to be agreed upon with the instructor.
   • The report must include:
     • Description of the study area and the environmental issue analyzed (e.g., deforestation monitoring, land use changes, water quality, extreme events, etc.).
     • Data used, specifying satellite sources (e.g., Sentinel, Landsat, MODIS) and the parameters analyzed.
     • Methodology applied, detailing image processing and classification techniques (pre-processing, multispectral analysis, vegetation indices, etc.).
     • Results and interpretation, including cartographic visualization and trend analysis.
   • The report must be submitted one week before the exam and will be discussed during the oral examination.

- manual of the theoretical part of the entire course

- manual of the practical practice of the entire course

- presentation, in PDF format, of each single theoretical lecture

- videolessons of all theoretical lectures (both in Italian and English)

- videolessons of all practical laboratory exercises (both in Italian and English)

- data and materials concerning the carrying out of laboratory exercises