Use of Satellite SAR Intensity Imagery for Detecting Building Areas Damaged Due to Earthquakes

2004 ◽  
Vol 20 (3) ◽  
pp. 975-994 ◽  
Author(s):  
Masashi Matsuoka ◽  
Fumio Yamazaki

Synthetic aperture radar (SAR) is remarkable for its capability to record the backscattering coefficient, the physical value of the earth's surface, regardless of weather condition or sun illumination. Therefore, SAR is a powerful tool that can be utilized to develop a universal method to comprehend damaged areas in disasters such as earthquakes, forest fires, and floods. We performed a feasibility study on backscattering characteristics of damaged areas in the 1995 Hyogoken-Nanbu (Kobe), Japan, earthquake using the pre- and post-event ERS images, revealing that the backscattering coefficient and intensity correlation between the two attained values were significantly lowered in hard-hit areas. The evaluation, however, was performed without speckle noise reduction. We also investigated the effects of speckle noise reduction and pixel-window size in evaluating building damage using the difference in the backscattering coefficient and correlation coefficient of the pre- and post-event ERS images. From the analysis, an optimum window size for the damage evaluation was obtained. It was also found that the accuracy of damage detection is not significantly improved for speckle-reduction filtering of window size larger than 21×21 pixels. We developed an automated method to detect hard-hit areas based on the discriminant analysis, and compared the detected distribution with a damage survey result.

2013 ◽  
Vol 325-326 ◽  
pp. 1584-1587
Author(s):  
Ming Wei Ji ◽  
Yan Li Liu ◽  
De Xiang Zhang

A novel and efficient speckle noise reduction algorithm based on wavelet transform by cycle spinning for removing speckle of unknown variance and minimizing the effect of pseudo-Gibbs phenomena from Synthetic Aperture Radar (SAR) images is proposed. Therefore, we show that the sub-band decompositions of logarithmically transformed SAR images. Then, we process and reconstruct multi-resolution wavelet coefficients by wavelet-threshold using cycle spinning, a technique estimating the true images as the linear average of individual estimates derived from wavelet thresholded translated versions of the noise images. Experimental results show that the proposed de-noising algorithm is possible to achieve an excellent balance between suppresses speckle effectively and weaken as many image Gibbs phenomena as possible. Quantitative and qualitative comparisons of the results obtained by the new method with the results achieved from the other speckle noise reduction techniques demonstrate its higher performance for speckle reduction in SAR images.


2016 ◽  
Vol 216 ◽  
pp. 502-513 ◽  
Author(s):  
Jun Liu ◽  
Ting-Zhu Huang ◽  
Gang Liu ◽  
Si Wang ◽  
Xiao-Guang Lv

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