REMOTE SENSING OF ENVIRONMENTAL SYSTEMS
Academic year2016/17
CourseTELECOMMUNICATIONS ENGINEERING
Code561II
Credits6
PeriodSemester 2
LanguageItalian
| Modules | Area | Type | Hours | Teacher(s) |
| SISTEMI DI TELERILEVAMENTO AMBIENTALE | ING-INF/03 | LEZIONI | 60 | |
Programma non disponibile nella lingua selezionata
Knowledge
The student who successfully completes the course will have the ability to understand the basic principles behind the complex world of remote sensing. He or she will be able to demonstrate a solid knowledge of remote sensing systems based on electro-optical sensors and of the methods used to process multispectral and hyperspectral images. He or she will be aware of the main signal processing aspects related to the remote sensing chain especially focusing on automatic techniques for object/material detection and extraction of thematic maps.
Assessment criteria of knowledge
During the laboratory practical demonstration, the student is asked to demonstrate his/her ability to write and run a MATLAB code that solves a practical remote sensing exercise (classification or detection).
During the oral exam, the student will be assessed on his/her ability in discussing the main course contents with competence, critical awareness and propriety of expression.
Methods:
- Final oral exam
- Final laboratory practical demonstration
Further information:
The final test is composed of a final laboratory practical demonstration followed by an oral exam. In general, each part contributes 50% to the definition of the final grade.
Teaching methods
Delivery: face to face
Learning activities:
- attending lectures
- preparation of oral/written report
- Laboratory work
Attendance: Advised
Teaching methods:
Syllabus
Generalities on remote sensing systems: the remote sensing chain leading from the radiance to the final products. Principles of radiometry. Models for at sensor radiance in the region of the e.m. spectrum spanning from Visible to InfraRed. The MODTRAN code. Preliminary analysis of multispectral and hyperspectral data. Supervised and unsupervised classification and application to satellite and airborne multispectral and hyperspectral images. Material detection in hyperspectral images: searching for "anomalies" or for materials characterised by a given spectrum.
Bibliography
Recommended reading includes the following works; further bibliography will be indicated.
[1] J. R. Schott, "Remote Sensing : The Image Chain Approach", Oxford Press, 2007.
[2] R. A. Schowengerdt, "Remote Sensing: models and methods for image processing,
II Ed.", Academic Press, 1997.
[3] J. A. Richards, X. Jia, "Remote Sensing Digital Image analysis: An
introduction, III Edition", Springer, 1999.
Updated: 14/11/2016 17:27
