Obtaining an accurate picture of large-scale natural disasters in metropolitan areas can be difficult. Although quick damage estimation systems such as strong ground motion monitoring and/or flow monitoring by utilities may be available, a time lag between the initial damage estimation and the actual damage assessment is unavoidable. Observations of damaged areas by helicopters, airplanes, and satellites provide information to fill in initial quick damage estimates with actual damage assessments that are timely, cover a large area, and have high accuracy, respectively. In particular, remote sensing by satellites can provide observations of a wide area with a single image, and it may be possible to use this technology to improve the accuracy of large-scale damage estimates.
This course focuses on the change (damage) detection algorithms by remotely sensed images. Particularly, the conventional and advanced image processing of optical and radar remote sensing are introduced to students who are interested in disaster management fields. The fundamental knowledge on the image processing of optical remote sensing, radar data acquisition and imaging, and their characteristics are learned. The principles of interferometric SAR (InSAR) and its application for measuring crustal movement due to natural disasters are also presented. Because sensors and observation systems are constantly advancing, the newest methodology in the field is also discussed. Students will have good understanding and basic skills of remote sensing in disaster management through this course.
By the end of this course, students will be able to:
1) Understand the remote sensing based damage detection methodologies and explain the examples of their application.
2) Explain the principles of radar remote sensing and synthetic aperture radar (SAR), and their characteristics.
3) Understand the interferometric process of SAR phase information and its application for disaster monitoring.
optical image, synthetic aperture radar (SAR), Interferometric SAR, image processing, damage detection
|Intercultural skills||Communication skills||Specialist skills||Critical thinking skills||Practical and/or problem-solving skills|
At the beginning of each class, key points of the previous class are reviewed. In the class, students are given exercise problems related to the lecture given that day to solve. To prepare for the class, students should read and check what topics will be covered from the materials uploaded on web site in advance. Required learning should be completed outside the classroom for understanding and review new technologies.
|Course schedule||Required learning|
|Class 1||Fundamentals of remote sensing for disaster management||Understand the overview of remote sensing technologies for disaster management|
|Class 2||Optical remote sensing for disaster monitoring #1||Understand the change (damage) detection methodologies using visual interpretation and pixel-based optical image processing|
|Class 3||Optical remote sensing for disaster monitoring #1||Understand the change (damage) detection methodologies using texture- and object-based optical image processing|
|Class 4||Fundamental of radar imaging||Understand the basic of radar observation and geometric characteristics of synthetic aperture radar (SAR)|
|Class 5||Characteristics of SAR image||Understand the SAR observation condition, calibration, polarimetry, and image pattern|
|Class 6||SAR image processing for disaster monitoring||Understand the damage detection using SAR intensity images|
|Class 7||Fundamental of interferometric SAR||Understand the interferometric process by SAR phase information|
|Class 8||Interferometric SAR application||Understand the interferometric SAR application for DEM generation and crustal deformation monitoring|
"Thomas M. Lillesand, Ralph W. Kiefer, Jonathan Chipman: Remote Sensing and Image Interpretation, sixth edition, John Wiley and Sons, Inc.,
Tutorial: Fundamentals of Remote Sensing: http://www.nrcan.gc.ca/earth-sciences/geomatics/satellite-imagery-air-photos/satellite-imagery-products/educational-resources/9309
mid-term report (30%) and final report (80%)
No required in advance