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Open AccessArticle

Two New Polarimetric Feature Parameters for the Recognition of the Different Kinds of Buildings in Earthquake-Stricken Areas Based on Entropy and Eigenvalues of PolSAR Decomposition

by Wei Zhai 1,2, Chunlin Huang 3,* and Wansheng Pei 3
1
Lanzhou Institute of Seismology, China Earthquake Administration, Lanzhou 730000, China
2
Key Laboratory of Loess Earthquake Engineering of China Earthquake Administration, Lanzhou 730000, China
3
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1613; https://doi.org/10.3390/rs10101613
Received: 30 July 2018 / Revised: 11 September 2018 / Accepted: 5 October 2018 / Published: 11 October 2018
Rapidly and accurately obtaining collapsed building information for earthquake-stricken areas can help to effectively guide the implementation of the emergency response and can reduce disaster losses and casualties. This work is focused on rapid building earthquake damage detection in urban areas using a single post-earthquake polarimetric synthetic aperture radar (PolSAR) image. In an earthquake-stricken area, the buildings include both damaged buildings and undamaged buildings. The undamaged buildings are made up of both parallel buildings, whose array direction is parallel to the flight direction, and oriented buildings, whose array direction is not parallel to the flight direction. The damaged buildings after an earthquake are made up of completely collapsed buildings and residual damaged parallel walls and oriented walls of the damaged buildings. Therefore, we divide the buildings in earthquake-stricken areas into five kinds: intact parallel buildings, damaged parallel walls, collapsed buildings, intact oriented buildings, and damaged oriented walls. The two new polarimetric feature parameters of λ_H and H_λ are proposed to recognize the five kinds of buildings, and the Wishart supervised classification method is employed to further improve the extraction accuracy of the damaged buildings and undamaged buildings. View Full-Text
Keywords: earthquake; PolSAR; collapsed buildings; damaged walls; polarimetric features earthquake; PolSAR; collapsed buildings; damaged walls; polarimetric features
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Zhai, W.; Huang, C.; Pei, W. Two New Polarimetric Feature Parameters for the Recognition of the Different Kinds of Buildings in Earthquake-Stricken Areas Based on Entropy and Eigenvalues of PolSAR Decomposition. Remote Sens. 2018, 10, 1613.

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