整合非均匀InSAR测量以绘制完整准确的三维地表位移:以2016年新西兰Mw 7.8 Kaiköura地震为例

J. Hu, J.H. Liu, L. X. Wu, Z. W. Li, Q. Sun
{"title":"整合非均匀InSAR测量以绘制完整准确的三维地表位移:以2016年新西兰Mw 7.8 Kaiköura地震为例","authors":"J. Hu, J.H. Liu, L. X. Wu, Z. W. Li, Q. Sun","doi":"10.23919/PIERS.2018.8597791","DOIUrl":null,"url":null,"abstract":"Three-dimensional (3-D) deformation fields associated with the 2016 Mw 7.8 Kaiköura earthquake in New Zealand are retrieved from SAR data acquired by ALOS-2 descending and Sentinel-1 ascending orbits based on the Pixel OffsetTracking technique In particular, a recently proposed method SM-VCE (Strain Model and Variance Component Estimation) is exploited to integrate the heterogeneous InSAR observations. The core idea of this method is exploiting the spatial correlation of the homogeneous points' deformations based on strain model, and determine the exact weights for the heterogeneous InSAR measurements by employing variance component estimation algorithm. The results reveal that the presented SM-VCE method is capable for the retrieval of complete and accurate 3-D deformation fields with respect to this event, which are highly consistent with the GNSS observations. In addition, accuracies of the used heterogeneous InSAR observations as well as the estimated 3-D deformations are quantitatively provided by the presented SM-VCE method.","PeriodicalId":355217,"journal":{"name":"2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Integration of Heterogeneous InSAR Measurements for Mapping Complete and Accurate Three-Dimensional Surface Displacements: A Case Study of 2016 Mw 7.8 Kaiköura Earthquake, New Zealand\",\"authors\":\"J. Hu, J.H. Liu, L. X. Wu, Z. W. Li, Q. Sun\",\"doi\":\"10.23919/PIERS.2018.8597791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three-dimensional (3-D) deformation fields associated with the 2016 Mw 7.8 Kaiköura earthquake in New Zealand are retrieved from SAR data acquired by ALOS-2 descending and Sentinel-1 ascending orbits based on the Pixel OffsetTracking technique In particular, a recently proposed method SM-VCE (Strain Model and Variance Component Estimation) is exploited to integrate the heterogeneous InSAR observations. The core idea of this method is exploiting the spatial correlation of the homogeneous points' deformations based on strain model, and determine the exact weights for the heterogeneous InSAR measurements by employing variance component estimation algorithm. The results reveal that the presented SM-VCE method is capable for the retrieval of complete and accurate 3-D deformation fields with respect to this event, which are highly consistent with the GNSS observations. In addition, accuracies of the used heterogeneous InSAR observations as well as the estimated 3-D deformations are quantitatively provided by the presented SM-VCE method.\",\"PeriodicalId\":355217,\"journal\":{\"name\":\"2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/PIERS.2018.8597791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/PIERS.2018.8597791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

基于像素偏移跟踪技术,从ALOS-2下降轨道和Sentinel-1上升轨道获取的SAR数据中提取2016年新西兰Mw 7.8 Kaiköura地震的三维变形场,特别是利用最近提出的一种方法(应变模型和方差分量估计)对非均匀InSAR观测数据进行整合。该方法的核心思想是基于应变模型,利用均匀点变形的空间相关性,利用方差分量估计算法确定非均匀InSAR测量的准确权重。结果表明,本文提出的SM-VCE方法能够完整准确地获取该事件的三维变形场,与GNSS观测结果高度一致。此外,本文提出的SM-VCE方法定量地提供了使用的非均匀InSAR观测的精度以及估计的三维变形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of Heterogeneous InSAR Measurements for Mapping Complete and Accurate Three-Dimensional Surface Displacements: A Case Study of 2016 Mw 7.8 Kaiköura Earthquake, New Zealand
Three-dimensional (3-D) deformation fields associated with the 2016 Mw 7.8 Kaiköura earthquake in New Zealand are retrieved from SAR data acquired by ALOS-2 descending and Sentinel-1 ascending orbits based on the Pixel OffsetTracking technique In particular, a recently proposed method SM-VCE (Strain Model and Variance Component Estimation) is exploited to integrate the heterogeneous InSAR observations. The core idea of this method is exploiting the spatial correlation of the homogeneous points' deformations based on strain model, and determine the exact weights for the heterogeneous InSAR measurements by employing variance component estimation algorithm. The results reveal that the presented SM-VCE method is capable for the retrieval of complete and accurate 3-D deformation fields with respect to this event, which are highly consistent with the GNSS observations. In addition, accuracies of the used heterogeneous InSAR observations as well as the estimated 3-D deformations are quantitatively provided by the presented SM-VCE method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信