基于时间序列InSAR和卡尔曼滤波的高家湾滑坡坡向变形演化分析

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2024-12-31 eCollection Date: 2024-01-01 DOI:10.1371/journal.pone.0316100
Jingchuan Yao, Runqing Zhan, Jiliang Guo, Wei Wang, Muce Yuan, Guangyu Li, Bo Zhang, Rui Zhang
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引用次数: 0

摘要

现有的滑坡监测方法无法准确反映滑坡体的真实变形,且单一SAR卫星的使用受其重访周期的影响,仍然存在滑坡监测时相分辨率不足的限制。为此,本文提出了一种基于升降轨道InSAR时间序列观测数据,利用卡尔曼滤波对高家湾滑坡沿坡变形进行动态重建和演化特征分析的方法。该方法首先在InSAR时间序列处理过程中采用网格选择方法,根据残差相位的标准差对相干点进行滤波,从而保证了提取相干点的密度和质量。随后,结合升降轨道数据,将滑坡的视线变形转化为沿坡变形。最后,利用卡尔曼滤波方法对滑坡变形进行动态重建,分析滑坡的演化特征,探讨其对交通基础设施的影响,从而显著提高滑坡监测的时间分辨率和精度。为验证算法的可行性,本文选取高家湾滑坡为典型研究区。基于2016 - 2023年Sentinel-1上升和下降SAR数据,提取坡体变形时间序列,进一步探讨其对坡体内部交通基础设施的影响。实验结果表明,将上升和下降SAR数据与卡尔曼滤波相结合,可以将滑坡监测的时间分辨率提高到6天。研究发现,2016年1月和2021年6月,坡体发生了两次明显滑移,其他时期相对稳定。进一步的讨论和分析表明,边坡上下部分的滑移变形速率和位错变形引起的剪应力存在差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evolutionary analysis of slope direction deformation in the Gaojiawan landslide based on time-series InSAR and Kalman filtering.

The existing landslide monitoring methods are unable to accurately reflect the true deformation of the landslide body, and the use of a single SAR satellite, affected by its revisit cycle, still suffers from the limitation of insufficient temporal resolution for landslide monitoring. Therefore, this paper proposes a method for the dynamic reconstruction and evolutionary characteristic analysis of the Gaojiawan landslide's along-slope deformation based on ascending and descending orbit time-series InSAR observations using Kalman filtering. Initially, the method employs a gridded selection approach during the InSAR time-series processing, filtering coherent points based on the standard deviation of residual phases, thereby ensuring the density and quality of the extracted coherent points. Subsequently, the combination of ascending and descending orbit data converts the landslide's line of sight (LOS) deformation into along-slope deformation. Finally, the Kalman filtering method is utilized for dynamic reconstruction of the landslide deformation, and an analysis of the evolutionary characteristics of the landslide is conducted to explore its impact on transportation infrastructure, thereby significantly improving the temporal resolution and accuracy of landslide monitoring. To verify the feasibility of the algorithm, this paper selects the Gaojiawan landslide as a typical study area. Based on the ascending and descending Sentinel-1 SAR data from 2016 to 2023, it extracts the temporal series of slope body deformation to further explore its impact on the internal transportation infrastructure of the slope body. Experimental results show that the combination of ascending and descending SAR data and Kalman filtering has improved the time resolution of landslide monitoring to six days. It was found that two significant slips occurred in the slope body in January 2016 and June 2021, while other periods were relatively stable. Further discussion and analysis reveal that there is a difference in the slip deformation rate between the upper and lower parts of the slope body, and the shear stress caused by dislocation deformation.

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来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
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