一种引入极化似然比检验的极化SAR滑坡形变监测方法

胡灿程; 汪长城; 沈鹏

doi:10.13203/j.whugis20200281

一种引入极化似然比检验的极化SAR滑坡形变监测方法

doi: 10.13203/j.whugis20200281

胡灿程^1,2,
汪长城^1, ,,
沈鹏¹

1 中南大学地球科学与信息物理学院, 湖南长沙, 410083;
2 广州市城市规划勘测设计研究院, 广东广州, 510000

基金项目:

国家自然科学基金（41671356）。

详细信息

作者简介:
胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

中图分类号: P237

A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

1 School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
2 Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510000, China

Funds:

The National Natural Science Foundation of China(41671356).

摘要: 相较于传统单极化SAR，全极化SAR（polarimetric synthetic aperture radar，PolSAR）能够获取更加丰富的地物目标极化散射信息，更全面地描述目标的几何物理特征。为了充分利用地物目标的极化散射信息，基于复Wishart分布的极化似然比检验原理（polarimetric likelihood ratio test，PolLRT），构建了极化似然比统计量来准确评价主从影像块之间的相似性。相比传统极化SAR偏移量跟踪方法而言，该方法不仅考虑了同种极化方式间的互相关信息，而且考虑了不同极化方式间的互相关信息，提高了极化信息匹配性能。最后，通过覆盖美国科罗拉多州Slumgullion滑坡的全极化UAVSAR（unmanned aerial vehicle SAR，UAVSAR）数据来开展实验，实验结果表明，算法具有更高的形变提取精度，并且在不同匹配窗口参数下表现出更加稳健的形变提取性能。
- 形变监测 /
- 极化似然比检验 /
- 极化合成孔径雷达
Abstract: Compared with the traditional single-polarization SAR, the full-polarization SAR can obtain more abundant polarimetric scattering information and describe the geometric and physical characteristics of the target more comprehensively. To make full use of the polarimetric scattering information of ground objects, the paper utilizes the polarimetric coherence matrix used to describe distributed targets and the polarimetric likelihood ratio test (PolLRT) based on complex Wishart distribution to accurately evaluate the temporal similarity between master and slave image blocks. Compared with the traditional method, the method not only considers the cross-correlation information between the same polarization, but also considers the cross-correlation information between different polarization modes, to improve the matching performance of the time series polarization information. Finally, in the real experiment, two fully polarized Unmanned Aerial Vehicle SAR (UAVSAR) data are used as the experimental data, and the external global positioning system (GPS) deformation data is used as the reference data. The experimental results show that the proposed algorithm has higher deformation extraction accuracy and shows more robust deformation extraction performance under different matching window sizes.
- deformation monitoring /
- polarimetric likelihood ratio test /
- polarimetric synthetic aperture radar

[1]	Van WestenC J, Van AschT W J, SoetersR. Landslide hazard and risk zonation-why is it still so difficult?[J].Bulletin of Engineering Geology and the Environment, 2006, 65(2):167-184
[2]	Harant O, BombrunL, VasileG, Ferro-FamilL, et al. Displacement estimation by maximum-likelihood texture tracking[J].IEEE Journal of Selected Topics in Signal Processing,2011, 5(3):398-407
[3]	GabrielA K, GoldsteinR M, ZebkerH A, Mapping small elevation changes over large areas:Differential radar interferometry[J]. Journal of Geophysical Research:Solid Earth, 1989, 94(1):9183-9191
[4]	MichelR, AvouacJ, TabouryJ, Measuring ground displacements from SAR amplitude images:Application to the Landers earthquake[J]. Geophysical Research Letters, 1999, 26(7):875-878
[5]	Michel R, TabouryJ, Measuring near field coseismic displacements from SAR images application to the Landers earthquake[J]. Geophysical Research Letters,1999, 26(19):3017-3020
[6]	ZhangL, LiaoM, BalzT, ShiX, JiangY. Monitoring Landslide Activities in the Three Gorges Area with Multi-frequency Satellite SAR Data Sets[J]. Modern Technologies for Landslide Monitoring and Prediction, 2015,181-208
[7]	HuJ, LiZW, DingXL, ZhuJJ. Two-dimensional co-seismic surface displacements field of the Chi-Chi earthquake inferred from SAR image matching[J]. Sensors, 2008, 8(10):6484-6495
[8]	CaiJ H, WangC C, MaoX K, WangQ. An adaptive offset tracking method with SAR images for landslide displacement monitoring[J].Remote Sensing, 2017, 9(8):830
[9]	WangC C, ShenP, LiX, ZhuJ, LiZ. A Novel Vessel Velocity Estimation Method Using Dual-Platform TerraSAR-X and TanDEM-X Full Polarimetric SAR Data in Pursuit Monostatic Mode[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(8):1-15
[10]	LeeJS, HoppelK W, MangoS. A, Miller A. R. Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery[J].IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(5):1017-1028
[11]	KorosovA, RampalP. A combination of feature tracking and pattern matching with optimal parametrization for sea ice drift retrieval from SAR data[J]. Remote Sensing, 2017, 9(3):258
[12]	TongX, et al. A novel subpixel phase correlation method using singular value decomposition and unified random sample consensus[J].IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(8):4143-4156
[13]	ErtenE, ReigberA, HellwichO, PratsP, Glacier velocity monitoring by maximum likelihood texture tracking[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(2):394-405
[14]	WangCC, MaoXK, WangQ J. Landslide displacement monitoring by a fully polarimetric SAR offset tracking method[J].Remote Sensing. 2016, 8(8):624
[15]	LeeJS, PottierE, Polarimetric radar imaging:from basics to applications[J]. International Journal of Remote Sensing. 2009, 33(1):333-334
[16]	ShenP, WangC, GaoH, ZhuJ, An adaptive nonlocal mean filter for PolSAR data with shape-adaptive patches matching, Sensors, 2018, 18(7):2215
[17]	DeledalleCA, DenisL, TupinF, ReigberA, JägerM. NL-SAR:A unified nonlocal framework for resolution-preserving (Pol)(In) SAR denoising, IEEE Transactions on Geoscience and Remote Sensing, 2014, 53(4):2021-2038
[18]	GoodmanN. R, Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction)[J]. Ann. Math. Stat., 1963, 34(1):152-177
[19]	ConradsenK, NielsenA. A, SchouJ, SkriverH, A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data[J].IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(1):4-19
[20]	ChenJ, ChenY, AnW, CuiY, YangJ, Nonlocal filtering for polarimetric SAR data:A pretest approach[J].IEEE Transactions on Geoscience and Remote Sensing, 2010,49(5):1744-1754
[21]	CrandellD. R, Movement of the Slumgullion earthflow near Lake City, Colorado[J]. Short Papers in the Geologic and Hydrologic Sciences, 1961, B136-B139
[22]	MililloP, FieldingE. J, ShulzW. H, DelbridgeB, BurgmannR, COSMO-SkyMed spotlight interferometry over rural areas:The Slumgullion landslide in Colorado, USA[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(7):2919-2926

[1]	朱同同, 史绪国, 周超, 蒋厚军, 张路, 廖明生. 利用2016—2020年Sentinel-1数据监测与分析三峡库区树坪滑坡稳定性 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20210247
[2]	蒲川豪, 许强, 赵宽耀, 蒋亚楠, 刘佳良, 寇平浪. 利用小基线集InSAR技术的延安新区地面抬升监测与分析 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20200262
[3]	王哲, 赵超英, 刘晓杰, 李滨. 西藏易贡滑坡演化光学遥感分析与InSAR形变监测 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20210168
[4]	蔡杰华, 张路, 董杰, 董秀军, 廖明生, 许强. 九寨沟震后滑坡隐患雷达遥感早期识别与形变监测 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20200263
[5]	赵超英, 刘晓杰, 张勤, 彭建兵, 许强. 甘肃黑方台黄土滑坡InSAR识别、监测与失稳模式研究 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20190072
[6]	刘琦, 岳国森, 丁孝兵, 杨坤, 冯光财, 熊志强. 佛山地铁沿线时序InSAR形变时空特征分析 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20190025
[7]	肖儒雅, 何秀凤. 时序InSAR水库大坝形变监测应用研究 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20170327
[8]	李达, 邓喀中, 高晓雄, 牛海鹏. 基于SBAS-InSAR的矿区地表沉降监测与分析 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20160566
[9]	杨杰, 常永雷, 李平湘, 赵伶俐, 史磊. 采用螺旋散射的SAR极化定标参考地物提取方法 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20180180
[10]	王云艳, 何楚, 涂峰, 陈东, 廖明生. 特征选择双层svm的融合算法用于极化sar图像分类 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j .whu g is20140351
[11]	赵磊, 陈尔学, 李增元, 冯琦, 李兰, 杨浩. 基于均值漂移和谱图分割的极化SAR影像分割方法及其评价 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20130681
[12]	陈德忠, 叶世榕, 刘炎炎, 刘郑. 基于观测值域的GPS多路径误差应用分析 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20120719
[13]	徐亚明, 王鹏, 周校, 邢诚. 地基干涉雷达IBIS-S桥梁动态形变监测研究 . 武汉大学学报 ● 信息科学版,
[14]	周志伟, 鄢子平, 刘苏, 李振洪. 永久散射体与短基线雷达干涉测量在城市地表形变中的应用 . 武汉大学学报 ● 信息科学版,
[15]	李德仁, 廖明生, 王艳. 永久散射体雷达干涉测量技术 . 武汉大学学报 ● 信息科学版,
[16]	蒋福珍. 重力测量在三峡库区形变监测中的作用 . 武汉大学学报 ● 信息科学版,
[17]	张小红, 李征航, 徐绍铨. 高精度GPS形变监测的新方法及模型研究 . 武汉大学学报 ● 信息科学版,
[18]	李征航, 吴云孙, 李振洪, 李英冰. 隔河岩大坝外观变形数据的处理和分析 . 武汉大学学报 ● 信息科学版,
[19]	鄂栋臣, 徐绍铨, 张松波, 王升定. 菲尔德斯海峡地壳断裂形变监测 . 武汉大学学报 ● 信息科学版,
[20]	罗天文, 李斐, 潘斌, 沈光保, 陈彤, 陈嘉明, 郝卫峰. 利用车载双天线InSAR系统监测公路边坡形变 . 武汉大学学报 ● 信息科学版, doi: 10.13203/j.whugis20200518

点击查看大图

计量

文章访问数: 36
HTML全文浏览量: 3
PDF下载量: 3
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

一种引入极化似然比检验的极化SAR滑坡形变监测方法

doi: 10.13203/j.whugis20200281

作者简介:
胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

计量

一种引入极化似然比检验的极化SAR滑坡形变监测方法

doi: 10.13203/j.whugis20200281

1 中南大学地球科学与信息物理学院, 湖南长沙, 410083;

2 广州市城市规划勘测设计研究院, 广东广州, 510000

作者简介:
胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

English Abstract

A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

1 School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;

2 Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510000, China

全文HTML

目录

留言板

一种引入极化似然比检验的极化SAR滑坡形变监测方法

doi: 10.13203/j.whugis20200281

作者简介: 胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

计量

出版历程

一种引入极化似然比检验的极化SAR滑坡形变监测方法

doi: 10.13203/j.whugis20200281

1 中南大学地球科学与信息物理学院, 湖南 长沙, 410083; 2 广州市城市规划勘测设计研究院, 广东 广州, 510000

作者简介: 胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

English Abstract

A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

1 School of Geosciences and Info-Physics, Central South University, Changsha 410083, China; 2 Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510000, China

全文HTML

目录

作者简介:
胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

1 中南大学地球科学与信息物理学院, 湖南长沙, 410083;

2 广州市城市规划勘测设计研究院, 广东广州, 510000

作者简介:
胡灿程,硕士生,主要研究方向为极化SAR滑坡形变监测。hucancheng@csu.edu.cn

1 School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;

2 Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510000, China