In order to evaluate the damage losses of future massive earthquakes, it is essential to compile and estimate shake-maps by using appropriate site characteristics of a wide area across administrative districts. Accurate evaluation of ground amplification characteristics requires detail soil profile information such as shear-wave velocity structures. It is pointed out, however, that approximate estimation of ground amplification is possible with the shear-wave velocity of the surface layer. The geomorphologic classification and average shear-wave velocity from the surface to 30 m depth (Vs30) estimated from geomorphological unit are introduced for mapping the amplification capabilities in this lecture. Based on the Grid and Web technologies, a near-realtime shake-map generation system, which provides wide and detail strong ground motion maps such as peak ground acceleration (PGA), peak ground velocity (PGV), and instrumental seismic intensity (INT) soon after an earthquake occurrence in and around Japan using combined usage of amplification capability map and observed seismic records, has been developed. This lecture also gives the specifications of the system.
Obtaining an accurate overview of large-scale natural disasters in metropolitan areas of developing countries 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 helicopter, airplane, and satellite 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. The damage detection algorithm using spaceborne Synthetic Aperture Radar (SAR) imagery and the examples of the integration of SAR images and seismic intensity information are presented for building damage estimation.

Masashi MATSUOKA

1 day(s)

Lecture Notes