scholarly journals Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data

2020 ◽  
Vol 12 (1) ◽  
pp. 137 ◽  
Author(s):  
Sang-Eun Park ◽  
Yoon Taek Jung

Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.

Author(s):  
J. Q. Zhao ◽  
J. Yang ◽  
P. X. Li ◽  
M. Y. Liu ◽  
Y. M. Shi

Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.


Author(s):  
J. Q. Zhao ◽  
J. Yang ◽  
P. X. Li ◽  
M. Y. Liu ◽  
Y. M. Shi

Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.


2012 ◽  
Vol E95.B (5) ◽  
pp. 1890-1893
Author(s):  
Wang LUO ◽  
Hongliang LI ◽  
Guanghui LIU ◽  
Guan GUI

2015 ◽  
Vol 54 (4) ◽  
pp. 934 ◽  
Author(s):  
Xiaochuan Zhang ◽  
Ge Yang ◽  
Nan Zhan ◽  
Hongwei Ji

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