SAR image visual optimization and building damage assessment based on polarimetric decomposition combination

doi:10.7523/j.issn.2095-6134.2020.06.005

›› 2020, Vol. 37 ›› Issue (6): 750-759.DOI: 10.7523/j.issn.2095-6134.2020.06.005

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SAR image visual optimization and building damage assessment based on polarimetric decomposition combination

LIU Shan^1,2,3, ZHANG Fengli^1,2,3, WEI Shiying⁴, LIU Na^1,2,3, SHAO Yun^1,2,3

1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Huzhou 313200, Zhejiang, China;
4. Beijing University of Civil Engineering and Architecture, Beijing 100044, China

Received:2019-03-27 Revised:2019-05-10 Online:2020-11-15

Abstract

Abstract: Building damage assessment is of great significance for disaster emergency monitoring. Polarimetric synthetic aperture radar (SAR) records the polarization scattering measurement matrix of ground objects and obtains abundant ground object information. Therefore it can be used for building damage assessment. Based on scattering characteristics of intact and damaged buildings, the scattering angle α_s1 in Touzi decomposition, the double-bounce scattering component in Yamaguchi decomposition after deorientation, and the symmetry|τ₂|in Touzi decomposition are combined for color composition and optimizing the polarimetric SAR image. This method can be used to quickly identify the building areas with different damage degrees by using single phase polarimetric SAR image. We take the March 11th,2011 earthquake that struck the coast of northeast Japan as an example and use quad-polarimetric ALOS PALSAR data acquired after the disaster for the analysis. The proposed method is verified by using RADARSAT-2 image of Wenchuan earthquake. The results show that the combination of polarimetric parameters not only optimizes the visual display effect of building targets, but also easily identifies the building areas with different damage degrees. This method greatly reduces the limitation and requirements for data source in disaster assessment.

Key words: Yamaguchi decomposition, Touzi decomposition, polarimetric SAR, buildings, damage assessment

CLC Number:

P237
TU746.1

LIU Shan, ZHANG Fengli, WEI Shiying, LIU Na, SHAO Yun. SAR image visual optimization and building damage assessment based on polarimetric decomposition combination[J]. , 2020, 37(6): 750-759.

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SAR image visual optimization and building damage assessment based on polarimetric decomposition combination

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