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Signature Analysis of Building Damage With TerraSAR-X New Staring SpotLight Mode Data

Lookup NU author(s): Dr Lixia Gong

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Abstract

In 2013, the TerraSAR-X (TSX) mission was extended by implementing two new modes, including Staring Spot-Light (ST). The azimuth resolution of this mode is significantly increased to approximately 0.24 m by widening the azimuth beam steering angle range. In this letter, five types of damaged buildings due to earthquake are analyzed using TSX images in the new ST mode. In particular, the characteristics of the individual damaged buildings are investigated using the new very high-resolution images. The old Beichuan County is selected as the research area, where most of the buildings damaged by the earthquake on May 12, 2008 have been preserved. Moreover, buildings with different types of damage can be found in the study area. Features such as backscattering and texture measurements of the damaged buildings in descending and ascending post-earthquake HH and VV polarization synthetic aperture radar (SAR) images are analyzed. Visual interpretation, statistical comparison, and classification experiments are performed for the damaged building analysis. Based on the analysis, the TSX ST mode images show potential for building damage detection and for discrimination of basic damage classes. In addition, the classification results show that the gray-level co-occurrence matrix (GLCM) second moment, the variance of backscattering, and the GLCM homogeneity are the three best features for the discrimination of damage type.


Publication metadata

Author(s): Wu F, Gong LX, Wang C, Zhang H, Zhang B, Xie L

Publication type: Article

Publication status: Published

Journal: IEEE Geoscience and Remote Sensing Letters

Year: 2016

Volume: 13

Issue: 11

Pages: 1696-1700

Print publication date: 01/11/2016

Online publication date: 16/09/2016

Acceptance date: 28/08/2016

ISSN (print): 1545-598X

ISSN (electronic): 1558-0571

Publisher: IEEE

URL: http://dx.doi.org/10.1109/LGRS.2016.2604841

DOI: 10.1109/LGRS.2016.2604841


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Funding

Funder referenceFunder name
41331176Key Program of National Natural Science Foundation of China
41371413National Natural Science Foundation of China

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