OVERVIEW

The couse covers the basic priciples of Remote Sensing such as the processing, enhancement and visualization of multispectral, hyperspectral and panchromatic data acquired with passive (optical) and active (radar) sensors. Applications are focussed, among the others, on geological studies on georesources, hazard and enviromment.

L'insegnamento tratta gli argomenti basilari del Telerilevamento come il processamento, il miglioramento e la visualizzazione di dati multispettrali, iperspettrali e pancromatici acquisiti con diversi sensori passivi (ottici) e attivi (radar) per applicazioni finalizzate a studi geologici, delle georisorse e dei rischi, ed in generale del territorio e dell’ambiente.

AIMS AND CONTENT

LEARNING OUTCOMES

The Remote sensing course focuses on the main aspects related to the analysis of remotely sensed images acquired both with passive and active sensors. The analyses will be aimed to the study of i) geology; ii) geo-resources and geohazard; iii) territory and environment. The aim of the course is to provide the basic culture to be able to select, to process and to interpret the proper satellite images for specific geological and geoenvironmental applications. For this purpose, the course includes both theoretical lessons on the basic principles of remote sensing and lab exercises on the spectral, radiometric and geometric characteristics of several satellite images.

AIMS AND LEARNING OUTCOMES

At the end of the course the student will be able to properly select satellite images and to develop effective strategy of image processing and enhancemennt for specific geological and geo-environmental studies.

Specifically the student will be able to:

- identify, select and download remote sensing data from public and open databese (e.g. USGS, ESA, NASA);

- perform image processing (e.g. spectral enhancement, convolution filtering, spectral index, principal component analysis, color transforms, pan sharpening, change detection);

- multi-temporal analyses;

- prepare tematic maps and perform supervised and unsupervised classifications;

- apply geometric corrections and georeferencing; 

-radar image processing and interferometric analyses

PREREQUISITES

Basic knowledge in Mathematics, Physics, Geology, and carthography acquired during the undergraduate degree courses.

TEACHING METHODS

The course includes both lectures in the classroom and practical excercises at DISTAV computer labs  where open source software will be used to process free and public satellite image dataset. Attendance to all planned activities is strongly recommended.  Test exercises will be carried out for evaluating the ongoing assessment of class learning. Please refer to the specific AulaWeb application for teaching for any update.

Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Sara Ferrando (sara.ferrando@unige.it), the Department’s disability liaison.

SYLLABUS/CONTENT

Origin of the Remote Sensing (RS). Introduction to optical RS. The role of RS for geo-environmental and geo-tectonic monitoring. EM spectrum and its interaction with different targets (e.g., water, vegetation, soils and rocks). Optical and radar sensors characteristics. Spatial resolution, spectral resolution, radiometric resolution, temporal resolution. Spectroradiometry: reflectance, transmittance, emittance. Interaction of the EMR with atmosphere.  Spectral signatures. Color theory and models. Characteristics of the panchromatic, multispectral and hyperspectral images. Multitemporal analyses. Local scale and regional scale image processing techniques: principal component analysis, data fusion, spectral indexes, convolution filtering, color transforms. Supervised and unsupervised classification. Geometric corrections and georeferencing. Active remote sensing in microwave: radar systems. Radar images and interferometry. Thermal images. Practical excercises at DISTAV computer labs using images acquired with different satellite sensor and airborne multispectral scanner.

RECOMMENDED READING/BIBLIOGRAPHY

Gomarasca M.A., 2004. Elementi di Geomatica. Ed. Associazione Italiana di Telerilevamento

S.A. Drury 2001. Image interpretation in Geology. Blackwell Science

Dessena M.A. e Melis M.T., 2006. Telerilevamento applicato. Mako edizioni

Sabins F.F., 2007. Remote Sensing: Principles and Interpretation. Waveland Press, Inc

Lillesand, Kiefer, Chapman, Remote sensing and image interpretation. 7° Ed. Wiley

Material presented during the class will be available in aulaweb.

TEACHERS AND EXAM BOARD

Exam Board

GABRIELE FERRETTI (President)

PAOLA CIANFARRA (President Substitute)

LESSONS

LESSONS START

Please refer to  https://easyacademy.unige.it/portalestudenti/

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists in an interview. The discussion is aimed at evaluating the topics covered during the course. 

Please refer to the specific AulaWeb application for teaching for any update.

ASSESSMENT METHODS

The interview covers the topics presented during the course and the critical discussion on the student's individual report prepared on specific applications of remote sensing.

Exam schedule

FURTHER INFORMATION

Continuous attendance at classes and course activities is strongly recommended.

Students with a certification of physical or learning disability filed with the University can find information on support services at the web page https://unige.it/disabilita-dsa/studenti-disturbi-specifici-apprendimento-dsa, provided by the “Services for the Inclusion of Students with Disabilities and with Learning Disorders." They can also contact Professor Sara Ferrando (sara.ferrando@unige.it), the Distav contact for disabilities