4.7 Article

Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image

期刊

REMOTE SENSING
卷 8, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/rs8030171

关键词

damage assessment; buildings; PolSAR; earthquake

资金

  1. Program for Changjiang Scholars and Innovative Research Team in University [IRT1278]
  2. Hundred Talent Program of the Chinese Academy of Sciences [29Y127D01]
  3. Cross-Disciplinary Collaborative Teams Program for Science, Technology and Innovation of the Chinese Academy of Sciences
  4. Earthquake Science and Technology Development Fund Program of Lanzhou Earthquake Research Institute
  5. China Earthquake Administration [2015M02]
  6. Object-Oriented High Trusted SAR Processing System of the National 863 Subject Program
  7. Airborne Multiband Polarimetric Interferometric SAR Mapping System of the National Major Surveying and Mapping Science and Technology Special Program

向作者/读者索取更多资源

After an earthquake, rapidly and accurately obtaining building damage information can help to effectively guide the implementation of the emergency rescue and can reduce disaster losses and casualties. Using a single post-earthquake fully-polarimetric synthetic aperture radar (PolSAR) image to interpret building damage information not only involves a guaranteed data source but is also easy and can be rapidly implemented. This paper is focused on rapid building earthquake damage detection in urban areas using post-earthquake PolSAR data. In PolSAR images, the undamaged buildings parallel to satellite flight pass are different from the collapsed buildings, but the undamaged buildings divergent to satellite flight pass are very similar to collapsed buildings because of their volume scattering characteristics. In this paper, the method of polarization orientation angle (POA) compensation is employed to increase the scattering power of buildings divergent to satellite flight pass, and then Wishart supervised classification is implemented on the PolSAR data after POA compensation. In addition, the two parameters of normalized difference of the dihedral component (NDDC) and rho(HHHV) are proposed to improve the classification accuracy of the Wishart supervised classification, and both the undamaged buildings and collapsed buildings are determined. The study was carried out after the 4.14 Yushu earthquake in Yushu County, Qinghai province, China. The three damage levels are set for the urban area at the city block scale according to the values of the BBCR building damage index. The experimental results confirm that the scheme proposed in this paper can greatly improve the accuracy of the extraction of building damage information.

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