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REMOTE SENSING OF NATURAL DISASTERS

CODE 94666
ACADEMIC YEAR 2022/2023
CREDITS
  • 5 cfu during the 2nd year of 10553 ENGINEERING FOR NATURAL RISK MANAGEMENT(LM-26) - SAVONA
  • SCIENTIFIC DISCIPLINARY SECTOR ING-INF/03
    LANGUAGE English
    TEACHING LOCATION
  • SAVONA
  • SEMESTER 1° Semester
    MODULES This unit is a module of:
    TEACHING MATERIALS AULAWEB

    AIMS AND CONTENT

    LEARNING OUTCOMES

    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; bio/geophysical parameter estimation through regression methods; and data representation in a geographic information system (GIS).

    AIMS AND LEARNING OUTCOMES

    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).

    TEACHING METHODS

    Class lectures and laboratory exercizes.

    SYLLABUS/CONTENT

    • Basic notions and terminology about sensors, platforms, and space orbits for Earth observation
    • Remote sensing image acquisition through passive sensors
    • Land cover mapping through remote sensing image classification
    • Detection of changes through multitemporal remote sensing image analysis
    • Bio/geophysical parameter estimation through regression from remote sensing data
    • Data representation in a geographic information system

    RECOMMENDED READING/BIBLIOGRAPHY

    • Richards J. A., Remote sensing digital image analysis, Springer, 2022
    • 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
    • Manolakis D. G., Lockwood R. B., and Cooley T. W., Hyperspectral imaging remote sensing, Cambridge University Press, 2016
    • Moser G., Analisi di immagini telerilevate per osservazione della Terra, ECIG, 2007
    • Sonka M., Hlavac V., Boyle R., Image processing, analysis, and machine vision, Cengage Learning, 2015
    • Class slides will be provided to the students through AulaWeb.

    TEACHERS AND EXAM BOARD

    Exam Board

    GABRIELE MOSER (President)

    SILVANA DELLEPIANE

    ALESSANDRO FEDELI

    LUCA MAGGIOLO

    MATTEO PASTORINO (President Substitute)

    ANDREA RANDAZZO (President Substitute)

    SEBASTIANO SERPICO (President Substitute)

    LESSONS

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    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.

    ASSESSMENT METHODS

    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.

    Exam schedule

    Date Time Location Type Notes
    21/12/2022 10:00 SAVONA Orale
    21/12/2022 10:00 SAVONA Orale
    25/01/2023 10:00 SAVONA Orale
    25/01/2023 10:00 SAVONA Orale
    15/02/2023 10:00 SAVONA Orale
    15/02/2023 10:00 SAVONA Orale
    05/06/2023 10:00 SAVONA Orale
    05/06/2023 10:00 SAVONA Orale
    26/06/2023 10:00 SAVONA Orale
    26/06/2023 10:00 SAVONA Orale
    13/09/2023 10:00 SAVONA Orale
    13/09/2023 10:00 SAVONA Orale