结合PolSAR影像纹理特征分析提取倒塌建筑物

doi:10.11873/j.issn.1004-0323.2016.5.0975

遥感技术与应用

2016, Vol. 31

Issue (5): 975-982 DOI: 10.11873/j.issn.1004-0323.2016.5.0975

遥感应用

结合PolSAR影像纹理特征分析提取倒塌建筑物

翟玮^1,2,3,4,5,沈焕锋⁶,黄春林^1,3,4

(1.中国科学院西北生态环境资源研究院，甘肃兰州 730000;2.中国科学院大学，北京 100049;
3.中国科学院西北生态环境资源研究院，甘肃省遥感重点实验室，甘肃兰州 730000;
4.中国科学院西北生态环境资源研究院，黑河遥感试验研究站，甘肃兰州 730000;
5.甘肃省地震局，甘肃兰州 730000;6.武汉大学资源与环境科学学院，湖北武汉 430079)

Collapsed Buildings Extraction from the PolSAR Image based on the Analysis of Texture Features

Zhai Wei^1,2,3,4,5,Shen Huanfeng⁶,Huang Chunlin^1,3,4

(1.Northwest Institute of Eco\|Environment and Resources,Chinese Academy
of Sciences,Lanzhou 730000,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China;
3.Key Laboratory of Remote Sensing of Gansu Province,Northwest Institute of Eco\|Environment
and Resources,Chinese Academy of Sciences,Lanzhou 730000,China;
4.Heihe Remote Sensing Experimental Research Station,Northwest Institute of Eco\|Environment
and Resources,Chinese Academy of Sciences,Lanzhou 730000,China;
5.Gansu Earthquake Administration,Lanzhou 730000,China;
6.School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China)

全文: PDF(7970 KB)

摘要：

利用震后1景极化SAR影像提取倒塌建筑物是一种快速有效的灾害调查手段。倒塌建筑和倾斜建筑物在PolSAR影像中的散射特征相似,易造成建筑物倒塌率的过度评估。由于倒塌建筑和倾斜建筑的纹理特征有较大差异,将利用这种纹理差异来解决倒塌建筑和倾斜建筑的混分问题。通过实验发现均值、同质性、熵及相关性4种基于灰度共生矩阵(Gray-Level Co\|occurrence Matrix,GLCM)的纹理特征能够有效区分倾斜建筑和倒塌建筑,故利用这4种纹理特征提取倒塌建筑中混杂的倾斜建筑,从而降低倒塌建筑的虚警率。以玉树地震为例,提取城区的建筑物震害信息,实验证明该方法能够大幅提高建筑物震害评估精度。


关键词： 全极化SAR; 震害评估; 倒塌建筑物; 纹理特征

Abstract:

Only using the post\|earthquake PolSAR imagery to interpret collapsed buildings information is a rapid and effective disaster investigation means.,but also is easy and fast for implementation.In PolSAR images,collapsed buildings and oblique undamaged buildings of which the orientation is unparallel to the radar flight direction all present volume scattering characteristics,and the over\|classification of collapsed buildings and the under-classification of undamaged buildings will be generated,which can lead to the excessive evaluation for disaster losses.Because of the difference of the significant texture features of the collapsed buildings and the oblique buildings,the difference of texture will be used to solve the problem of the mixing of the collapsed building and the oblique building.After research and analysis,collapsed buildings and oblique buildings can be well distinguished by their differences in the four texture feature parameters of Mean,Homogeneity,Entropy,and Correlation based on Gray-Level Co-occurrence Matrix (GLCM).Therefore,in order to reduce the false alarm rate of collapsed buildings,the four kinds of texture feature will be used to extract the oblique buildings and collapsed buildings.In this work,the Yushu earthquake was taken as example,and building earthquake damage information in urban region were extracted.The experimental results show that the proposed method can greatly increase the building earthquake damage assessment accuracy.

Key words: Full polarimetric SAR Earthquake damage assessment Collapsed buildings Texture features

收稿日期: 2016-01-29 出版日期: 2016-11-25

P 237

基金资助:

中国科学院“百人计划”项目“寒旱区地表水文关键要素的多源遥感数据同化研究”(29Y127D01)和甘肃省地震局地震科技发展基金“基于极化雷达的建筑物震害识别研究”(2015M02)资助。

通讯作者: 黄春林(1979-)，男，宁夏青铜峡人，研究员,主要从事陆面数据同化和定量遥感方面的研究。Email:huangcl@lzb.ac.cn。

作者简介: 翟玮(1981-)，女，甘肃白银人，博士研究生,主要从事雷达遥感建筑物震害研究。Email:zwxzzzdsyhq@163.com。

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引用本文:

翟玮,沈焕锋,黄春林. 结合PolSAR影像纹理特征分析提取倒塌建筑物[J]. 遥感技术与应用, 2016, 31(5): 975-982.

Zhai Wei,Shen Huanfeng,Huang Chunlin. Collapsed Buildings Extraction from the PolSAR Image based on the Analysis of Texture Features. Remote Sensing Technology and Application, 2016, 31(5): 975-982.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.5.0975 或 http://www.rsta.ac.cn/CN/Y2016/V31/I5/975

［1］Yang Ning.Preliminary Disscusion on Geophysical Exploration Methods in the Construction of Seismic Design and the Role Played in Construction Testing［J］.China Inestigation & Design,2009,8:65-68.［杨宁.浅议物探方法在建筑抗震设计和施工检测中的作用［J］.中国勘察设计,2009,8:65-68.］

［2］Xu Pengjie,Deng Lei.Application of Remote Sensing in the Field of Disaster Reduction and Response［J］.Remote Sensing Technology and Application,2011,26(4):512-519.［徐鹏杰,邓磊.遥感技术在减灾救灾中的应用［J］.遥感技术与应用,2011,26(4):512-519.］

［3］Zhai W,Shen H F,Huang C L,et al.Building Earthquake Damage Information Extraction from a Single Post-earthquake PolSAR Image［J］.Remote Sensing,2016,8(3):171.

［4］Zhai W,Shen H F,Huang C L,et al.Fusion of Polarimetric and Texture Information for Urban Building Extraction from Fully Polarimetric SAR Imagery［J］.Remote Sensing Letters,2016,7(1):31-40.

［5］Chen S W,Li Y Z,Xing S Q,et al.Urban Damage Evaluation Using Polarimetric SAR Data［C］//2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),Quebec,Canada,2014:2754-2757.

［6］Chen S W,Sato M.Tsunami Damage Investigation of Built-up Areas Using Multitemporal Spaceborne Full Polarimetric SAR Images［J］.IEEE Transactions on Geoscience and Remote Sensing,2013,51(4):1985-1997.

［7］Park S E,Yamaguchi Y,Singh G,et al.Polarimetric SAR Remote Sensing of Earthquake/Tsunami disaster［C］//2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),Munich,Germany,2012:1170-1173.

［8］Park S E,Yamaguchi Y,Kim D.Polarimetric SAR Remote Sensing of the 2011 Tohoku Earthquake Using ALOS/PALSAR［J］.Remote Sensing of Environment,2013,132:212-220.［9］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.

［10］Watanabe M,Motohka T,Miyagi Y,et al.Analysis of Urban Areas Affected by the 2011 off the Pacific Coast of Tohoku Earthquake and Tsunami with L-band SAR Full-polarimetric Mode［J］.IEEE Geoscience and Remote Sensing Letters,2012,9(3):472-476.

［11］Yamaguchi Y.Disaster Monitoring by Fully Polarimetric SAR Data Acquired with ALOS-PALSAR［J］.Proceedings of the IEEE,2012,100(10):2851-2860.

［12］Li X,Guo H,Zhang L,et al.A New Approach to Collapsed Building Extraction Using Radarsat-2 Polarimetric SAR Imagery［J］.IEEE Geoscience and Remote Sensing Letters,2012,9(4):677-681.

［13］Guo H,Liu L,Zhang L,et al.Earth Observation for Earthquake Disaster Monitoring and Assessment［M］.Sebastiano D'Amico.Earthquake Research and Analysis-Statistical Studies,Observations and Planning.Croatia:INTECH Open Access Publisher,2012:293-312.

［14］Zhao L,Yang J,Li P,et al.Damage Assessment in Urban Areas Using Post-earthquake Airborne PolSAR Imagery［J］.International Journal of Remote Sensing,2013,34(24):8952-8966.

［15］Shen Juncheng,Xu Xin,Dong Hao,et al.Collapsed Building Extraction from Single Full Polarimetric SAR Image after Earthquake［J］.Science Technology and Engineering,2015,15(14):86-91.［沈俊成,徐新,董浩,等.震后单幅全极化SAR图像中倒塌建筑提取研究［J］.科学技术与工程,2015,15(14):86-91.］

［16］Haralick R M,Shanmugam K,Dinstein I H.Textural Features for Image Classification［J］.IEEE Transactions on Systems,Man and Cybernetics,1973,6:610-621.

［17］Yamaguchi Y,Moriyama T,Ishido M,et al.Four-component Scattering Model for Polarimetric SAR Image Decomposition［J］.IEEE Transactions on Geoscience and Remote Sensing,2005,43(8):1699-1706.

［18］Yamaguchi Y,Yajima Y,Yamada H.A Four-component Decomposition of POLSAR Images based on the Coherency Matrix［J］.IEEE Geoscience and Remote Sensing Letters,2006,3(3):292-296.

［19］Wang Chao,Zhang Hong,Chen Xi,et al.Image Processing of Fully Polarimetric Synthetic Aperture Radar［M］.Beijing:Science Press,2008:97-99.［王超,张红,陈曦,等.全极化合成孔径雷达图像处理［M］.北京:科学出版社,2008:97-99.］

［20］Xu Jia,Chen Yuanyuan,Huang Qihuan,et al.Built-up Areas Extraction in High Resolution Spaceborne SAR Image based on the Integration of Grey and Texture Features［J］.Remote Sensing Technology and Application,2012,27(5):692-698.［徐佳,陈媛媛,黄其欢,等.综合灰度与纹理特征的高分辨率星载SAR图像建筑区提取方法研究［J］.遥感技术与应用,2012,27(5):692-698.］

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