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基于多干涉合成孔径雷达技术的公路变形监测

Highway Deformation Monitoring by Multiple InSAR Technology.

作者信息

Zhao Dan, Yao Haonan, Gu Xingyu

机构信息

College of Transportation, Southeast University, Nanjing 211100, China.

出版信息

Sensors (Basel). 2024 May 8;24(10):2988. doi: 10.3390/s24102988.

Abstract

Addressing the challenge of large-scale uneven deformation and the complexities of monitoring road conditions, this study focuses on a segment of the G15 Coastal Highway in Jiangsu Province. It employs PS-InSAR, SBAS-InSAR, and DS-InSAR techniques to comprehensively observe deformation. Analysis of 73 image datasets spanning 2018 to 2021 enables separate derivation of deformation data using distinct InSAR methodologies. Results are then interpreted alongside geological and geomorphological features. Findings indicate widespread deformation along the G15 Coastal Highway, notably significant settlement near Guanyun North Hub and uplift near Guhe Bridge. Maximum deformation rates exceeding 10 mm/year are observed in adjacent areas by all three techniques. To assess data consistency across techniques, identical observation points are identified, and correlation and difference analyses are conducted using statistical software. Results reveal a high correlation between the monitoring outcomes of the three techniques, with an average observation difference of less than 2 mm/year. This underscores the feasibility of employing a combination of these InSAR techniques for road deformation monitoring, offering a reliable approach for establishing real-time monitoring systems and serving as a foundation for ongoing road health assessments.

摘要

针对大规模不均匀变形的挑战以及道路状况监测的复杂性,本研究聚焦于江苏省G15沿海高速公路的一段。它采用永久散射体合成孔径雷达干涉测量(PS-InSAR)、小基线集合成孔径雷达干涉测量(SBAS-InSAR)和分布式散射体合成孔径雷达干涉测量(DS-InSAR)技术来全面观测变形。对2018年至2021年的73个图像数据集进行分析,能够使用不同的合成孔径雷达干涉测量方法分别导出变形数据。然后结合地质和地貌特征对结果进行解释。研究结果表明,G15沿海高速公路沿线存在广泛的变形,特别是灌云北枢纽附近沉降显著,古河桥附近隆起。所有三种技术在相邻区域均观测到最大变形速率超过10毫米/年。为评估不同技术间的数据一致性,确定了相同的观测点,并使用统计软件进行相关性和差异分析。结果显示,三种技术的监测结果具有高度相关性,平均观测差异小于2毫米/年。这突出了采用这些合成孔径雷达干涉测量技术组合进行道路变形监测的可行性,为建立实时监测系统提供了可靠方法,并为持续的道路健康评估奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1334/11124978/675ec3831b93/sensors-24-02988-g001.jpg

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