The course introduces the key concepts related to information extraction from remote sensing images in the framework of disaster risk prevention and assessment. Basic knowledge will be provided about remote sensing image acquisition through passive sensors; land cover mapping through remote sensing image classification in the application to risk prevention; detection of ground changes from multitemporal remote sensing images in the application to damage assessment; and data representation in a geographic information system (GIS).
After the course, the student shall know the key concepts related to information extraction from remote sensing images in the framework of disaster risk prevention and assessment. He/she shall have basic knowledge about: remote sensing images; land cover mapping through remote sensing image classification in the application to risk prevention; detection of ground changes from multitemporal remote sensing images in the application to damage assessment; bio/geophysical parameter estimation through regression from remote sensing data; and data representation in a geographic information system (GIS). In this framework, he/she shall also have methodological bases about machine learning for supervised classification and regression.
Class lectures and laboratory exercizes.
This course also contributes to the achievement of the following Sustainable Development Goals of the UN 2030 Agenda: Objectives no. 4, 8, 13, and 15.
Ricevimento: By appointment
Ricevimento: By appointment.
GABRIELE MOSER (President)
SILVANA DELLEPIANE
ALESSANDRO FEDELI
LUCA MAGGIOLO
ROOZBEH RAJABI TOOSTANI
ANDREA RANDAZZO (President Substitute)
SEBASTIANO SERPICO (President Substitute)
https://courses.unige.it/10553/p/students-timetable
Oral examination on the topics included in the syllabus of the course.
Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities.
Within the oral examination, the student's knowledge of the course topics and his/her capability to discuss how to address simple problems of remote sensing data analysis associated with disaster risk prevention and management shall be evaluated.