基于极化分解组合的SAR图像视觉优化和建筑物损毁评估

doi:10.7523/j.issn.2095-6134.2020.06.005

中国科学院大学学报 ›› 2020, Vol. 37 ›› Issue (6): 750-759.DOI: 10.7523/j.issn.2095-6134.2020.06.005

基于极化分解组合的SAR图像视觉优化和建筑物损毁评估

刘杉^1,2,3, 张风丽^1,2,3, 韦诗莹⁴, 刘娜^1,2,3, 邵芸^1,2,3

1. 中国科学院遥感与数字地球研究所, 北京 100094;
2. 中国科学院大学, 北京 100049;
3. 中科卫星应用德清研究院微波目标特性测量与遥感重点实验室, 浙江湖州 313200;
4. 北京建筑大学, 北京 100044

收稿日期:2019-03-27 修回日期:2019-05-10 发布日期:2020-11-15
通讯作者: 张风丽
基金资助:
国家重点研发计划（2016YFB0502504）和国家自然科学基金（41671359，61471358）资助

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 Published:2020-11-15

摘要/Abstract

摘要： 建筑物损毁评估对灾害应急监测具有重要意义。极化SAR图像蕴含丰富的地物信息，并且记录有目标地物的极化散射矩阵，可用于建筑物的损毁评估。针对完好和损毁建筑物两类目标的散射特征，利用Touzi分解散射角α_s1、去定向后Yamaguchi分解二次散射分量和Touzi分解散射对称度|τ₂|进行RGB彩色合成，对极化SAR图像进行视觉优化，进而利用单一时相SAR图像快速识别出不同损毁程度的建筑物区域。以2011年3月11日发生在日本东北部海域的地震为例，利用灾后的ALOS PALSAR全极化数据开展实验分析，并利用汶川地震RADARSAT-2图像对提出的方法进行验证。结果表明，通过对极化参量的组合不仅可以优化建筑物目标的视觉显示效果，同时可提高不同损毁程度建筑物区域识别度，从而大大降低灾害评估对于数据源的限制和要求。

关键词: Yamaguchi分解, Touzi分解, 全极化SAR, 建筑物, 损毁评估

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

中图分类号:

P237
TU746.1

刘杉, 张风丽, 韦诗莹, 刘娜, 邵芸. 基于极化分解组合的SAR图像视觉优化和建筑物损毁评估[J]. 中国科学院大学学报, 2020, 37(6): 750-759.

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.

参考文献

[1] Hao H M, Zhang Y H, Shi H Y. Application of test statistic method in fully polarimtric SAR change detection[J]. Journal of Remote Sensing, 2012, 16(3):520-532.
[2] Shen J C, Xu X, Dong H, et al. Collapsed building extraction from single full polarimetric SAR image after earthquake[J]. Science Technology and Engineering, 2015, 15(14):86-91.
[3] 王庆. 基于极化SAR的建筑物震害信息提取研究[D]. 北京:北京大学, 2014.
[4] 闫丽丽. 基于散射特征的极化SAR影像建筑物提取研究[D]. 北京:中国矿业大学(北京), 2013.
[5] 孙萍. 极化SAR图像建筑物提取方法研究[D]. 北京:首都师范大学, 2013.
[6] Wang X Q, Jin D J, Dou A. Study on the fractal analysis of SAR images and its application to the extraction of seismic damage of 2010 Yushu, China Ms=7.1 earthquake[C]//Sato M. Geoscience and Remote Sensing. Vancouver:IEEE, 2011:1981-1984.
[7] Guo H D, Li X W, Zhang L. Study of detecting method with advanced airborne and spaceborne synthetic aperture radar data for collapsed urban buildings from the Wenchuan earthquake[J]. Journal of Applied Remote Sensing, 2009, 3(1):131-136.
[8] Li X W, Guo H D, Zhang L, et al. A new approach to collapsed building extraction using RADARSAT-2 polarimetric SAR imagery[J]. IEEE Geoscience & Remote Sensing Letters, 2012, 9(4):677-681.
[9] Zhang H Z, Wang Q, Zeng Q M, et al. A novel approach to building collapse detection from post-seismic polarimetric SAR imagery by using optimization of polarimetric contrast enhancement[C]//2015 IEEE International Geoscience and Remote Sensing Symposium. Milan:IEEE, 2015, 3270-3273.
[10] Chen S W, Sato M. Tsunami damage investigation of built-up areas using multitemporal spaceborne full polarimetric SAR images[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013, 51(4):1985-1997.
[11] Sato M, Chen S W, Satake M. Polarimetric SAR analysis of tsunami damage following the March 11, 2011 East Japan earthquake[J]. Proceedings of the IEEE, 2012, 100(10):2861-2875.
[12] Bhattacharya A, Touzi R. Polarimetric SAR urban classification using the Touzi target scattering decomposition[J]. Canadian Journal of Remote Sensing, 2012, 37(4):323-332.
[13] Yamaguchi Y, Moriyama T, Ishido M, et al. Four-component scattering model for polarimetric SAR image decomposition[J]. IEEE Transactions on Geoscience & Remote Sensing, 2005, 43(8):1699-1706.
[14] An W, Yi C, Jian Y. Three-component model-based decomposition for polarimetric SAR data[J]. IEEE Transactions on Geoscience & Remote Sensing, 2010, 48(6):2732-2739.
[15] Yamaguchi Y, Sato A, Boerner W M, et al. Four-component scattering power decomposition with rotation of coherency matrix[J]. IEEE Transactions on Geoscience & Remote Sensing, 2010, 49(6):2251-2258.
[16] 安文韬. 基于极化SAR的目标极化分解与散射特征提取研究[D]. 北京:清华大学, 2010.
[17] Touzi R. Target scattering decomposition in terms of roll-invariant target parameters[J]. IEEE Transactions on Geoscience & Remote Sensing, 2006, 45(1):73-84.
[18] Cloude S R. Group theory and polarisation algebra[J]. Optik, 1986, 75:26-36.
[19] Li K, Shao Y, Touzi R, et al. Rice monitoring using touzi decomposition based on polarimetric SAR data in Southwestern China[C]//Brisco B. Progress in Electromagnetics Research Symposium. Suzhou:The Electromagnetics Academy, 2011:827-830.

基于极化分解组合的SAR图像视觉优化和建筑物损毁评估

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

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

本文评价

访问统计

联系我们

[1]	杨牡丹, 魏中浩, 徐志林, 张冰尘, 洪文. 一种基于层次稀疏的全极化SAR层析成像方法[J]. 中国科学院大学学报, 2020, 37(4): 525-531.
[2]	马肖肖, 程博, 刘岳明, 崔师爱, 梁琛彬. 基于极化特征和纹理特征的PolSAR影像建筑物提取方法[J]. 中国科学院大学学报, 2019, 36(5): 682-693.
[3]	贾莹玉, 刘士彬, 段建波, 谢帅. 结合质量控制的震后房屋倒塌众包评估模型[J]. 中国科学院大学学报, 2019, 36(3): 354-362.
[4]	李亮, 王成, 李世华, 习晓环. 基于机载LiDAR数据的建筑屋顶点云提取方法[J]. 中国科学院大学学报, 2016, 33(4): 537-541.
[5]	尤红建, 李树楷. 基于稀疏激光采样点的建筑物提取[J]. 中国科学院大学学报, 2001, 18(2): 154-159.