洞庭湖软土区域时序InSAR形变与环境物理参数联合估计方法

doi:10.11947/j.AGCS.2023.20220287

测绘学报 ›› 2023, Vol. 52 ›› Issue (12): 2127-2140.doi: 10.11947/j.AGCS.2023.20220287

洞庭湖软土区域时序InSAR形变与环境物理参数联合估计方法

朱珺¹, 朱凌杰^1,2, 邢学敏^1,3, 张锐¹, 鲍亮¹, 张腾飞¹, 鲍皓丹^1,3

1. 长沙理工大学交通运输工程学院, 湖南长沙 410114;
2. 中南大学地球科学与信息物理学院, 湖南长沙 410083;
3. 洞庭湖生态环境遥感监测湖南省重点实验室, 湖南长沙 410114

收稿日期:2022-05-25 修回日期:2022-08-03 发布日期:2024-01-03
通讯作者: 邢学敏 E-mail:xuemin.xing@csu.edu.cn
作者简介:朱珺(1986-),男,博士,讲师,研究方向为时序InSAR形变监测、PolInSAR沙漠地区穿透深度反演。E-mail:jzhu@csust.edu.cn
基金资助:
国家自然科学基金(42374046;42330717;42074033;51878078;41701536;41904003;61701047);湖南省自然科学基金(2022JJ30589;2019JJ50639;2020JJ5571);湖南省教育厅重点项目(18A148);洞庭湖生态环境遥感监测湖南省重点实验室开放课题(2021-011);湖南省交通运输厅科技创新项目(202211);长沙市杰出创新青年培养计划项目(kq2209011);中国水利水电第八工程局有限公司科研项目(2023060);湖南省自然资源厅科技计划项目(20230118CH);长沙理工大学大学生研究性学习与创新实验计划项目

Joint estimation method of time-series InSAR deformation and environmental physical parameters for soft clay area over Dongting lake

ZHU Jun¹, ZHU Lingjie^1,2, XING Xuemin^1,3, ZHANG Rui¹, BAO Liang¹, ZHANG Tengfei¹, BAO Haodan^1,3

1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China;
2. School of Geosciences and Info-physics, Central South University, Changsha 410083, China;
3. Hunan Key Laboratory of Remote Sensing of Ecological Environment in Dongting Lake Area, Changsha 410114, China

Received:2022-05-25 Revised:2022-08-03 Published:2024-01-03
Supported by:
The National Natural Science Foundation of China (Nos. 42374046;42330717;42074033;51878078;41701536;41904003;61701047);The Natural Science Foundation of Hunan Province (Nos. 2022JJ30589;2019JJ50639;2020JJ5571);Key Projects of Hunan Provincial Department of Education (No.18A148);Hunan Key Laboratory of Remote Sensing of Ecological Environmentint in Dongting Lake Area's Open Project (No. 2021-011);Science and Technology Innovation Project of Hunan Provincial Department of Transportation (No. 202211);Changsha Innovation Talent Promotion Plan Project for Distinguished Young Scholar (No. kq2209011);Research Project of Sinohydro Engineering Bureau 8 Co., Ltd. (No. 2023060);Research Foundation of the Department of Natural Resources of Hunan Province (No. 20230118CH);Changsha University of Science and Technology Students' Research Learning and Innovative Experimental Program Project

摘要/Abstract

摘要： 洞庭湖生态经济区是国家级重要发展片区,是国家战略发展的重要部分,但洞庭湖区域土质以软土为主,必须对区域内密集分布的基础设施开展长期持续的安全稳定性监测。目前使用PSInSAR进行监测时普遍是采用线性速率模型,但洞庭湖软土区域基础设施形变随时间演化具有明显的非线性特征,并且还受热膨胀、降水等环境物理因素影响。针对这一问题,本文提出一种用PSInSAR同时估计变形和环境物理参数的方法。该方法利用洞庭湖软土形变预测的双曲线模型和热膨胀效应先验模型代替原方法中的线性速率模型,同时融入热膨胀参数和环境降水参数,在PSInSAR解算过程中将形变与环境物理参数一并求解。在此基础上本文还提出了基于LAMDBA-SVD的时间维参数估计和基于雅可比迭代的空间维参数估计的解算策略。试验选取了覆盖岳阳市洞庭湖区的24景TerraSAR-X雷达卫星遥感影像,设计了包含PS点选点、基线网络构建、InSAR时序建模、时空维参数估计、时序总形变的生成这一完整算法流程,获取了此区域典型基础设施的热膨胀系数,以及2011年12月至2013年4月的时间序列形变场。利用模型的残余相位来评估建模精度,结果显示本文方法的残余相位为0.4 rad,相比传统线性速率模型提升了36.5%。

关键词: 合成孔径雷达干涉测量, 软土, 热膨胀, 基础设施, 形变监测

Abstract: The Dongting lake eco-economic zone is an important national development zone and an important part of national strategic development, but the soils of the Dongting lake region are predominantly soft clay, and long-term continuous safety and stability monitoring of the densely distributed infrastructure in the region is necessary. The current monitoring using PSInSAR is generally based on a linear rate model, but infrastructure deformation in the Dongting lake soft soil region has obvious non-linear characteristics over time and is also influenced by environmental physical factors such as thermal expansion and precipitation. To address this problem, this paper proposes a method for estimating deformation and environmental physical parameters simultaneously using PSInSAR. The method uses the hyperbolic model and the a priori model of thermal expansion effect for the prediction of the deformation of soft soil in Dongting lake instead of the linear rate model in the original method, incorporates both thermal expansion parameters and environmental precipitation parameters, and solves the deformation and environmental physical parameters together in the PSInSAR solution process. The paper also proposes a solution strategy for LAMDBA-SVD-based time-dimensional parameter estimation and Jacobi iteration-based spatial-dimensional parameter estimation. Totally 24 TerraSAR-X radar satellite remote sensing image covering the Dongting lake area in Yueyang city, China, were selected for experiment, and the thermal expansion parameter of the typical infrastructures in this area was obtained and the time-series deformation from November 2011 to April 2013 was generated by the proposed method. The residual phase of the model is used to evaluate the modeling accuracy of the new algorithm. The results show that the residual phase of the improved model is 0.4 rad, with a 36.5% increasement compared to the traditional linear rate model.

Key words: InSAR, soft clay, thermal expansion, infrastructure, deformation monitoring

中图分类号:

P237

朱珺, 朱凌杰, 邢学敏, 张锐, 鲍亮, 张腾飞, 鲍皓丹. 洞庭湖软土区域时序InSAR形变与环境物理参数联合估计方法[J]. 测绘学报, 2023, 52(12): 2127-2140.

ZHU Jun, ZHU Lingjie, XING Xuemin, ZHANG Rui, BAO Liang, ZHANG Tengfei, BAO Haodan. Joint estimation method of time-series InSAR deformation and environmental physical parameters for soft clay area over Dongting lake[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(12): 2127-2140.

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洞庭湖软土区域时序InSAR形变与环境物理参数联合估计方法

Joint estimation method of time-series InSAR deformation and environmental physical parameters for soft clay area over Dongting lake

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