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 and shall be able to apply, through dedicated software platforms, 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; and data representation in a geographic information system (GIS).
Class lectures (approximately 32 hours) and laboratory exercizes (approximately 8 hours)
Richards J. A., Remote sensing digital image analysis, Springer, 2013 Bishop C., Pattern recognition and machine learning, Springer, 2006 Campbell J. B. and Wynne R. H., Introduction to remote sensing, Guilford Press, 2011 Hastie T., Tibshirani R., and Friedman J., The elements of statistical learning, Springer, 2008 Long D. and Ulaby F. T., Microwave radar and radiometric remote sensing, Artech House, 2015 Moser G., Analisi di immagini telerilevate per osservazione della Terra, ECIG, 2007 Class slides will be provided to the students through AulaWeb.
Ricevimento: By appointment
GABRIELE MOSER (President)
MATTEO PASTORINO (President)
SEBASTIANO SERPICO (President)
ANDREA DE GIORGI
SILVANA DELLEPIANE
ALESSANDRO FEDELI
LUCA MAGGIOLO
ANDREA RANDAZZO
DAVID SOLARNA
REMOTE SENSING OF NATURAL DISASTERS
Oral examination
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.
