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    顾及非线性蠕变特征的黄土填方区InSAR沉降监测方法

    An InSAR-based method considering nonlinear creep behavior for monitoring land subsidence in loess-filled areas

    • 摘要: 针对黄土填方区沉降演化机制复杂以及传统时序合成孔径雷达干涉测量(interferometry synthetic aperture Radar,InSAR)线性模型难以监测非线性蠕变的问题,该文提出一种顾及非线性蠕变特征的黄土填方区InSAR沉降监测方法。该方法采用自适应切线角变化阈值法检测并分段估计填方分布与填方厚度,在小基线集InSAR(small baseline subset InSAR,SBAS-InSAR)算法框架下,融合基于分数阶微积分理论的黄土非线性蠕变本构方程与差分干涉相位模型,并利用切尔诺贝利灾难算法(Chernobyl disaster optimization,CDO)估计蠕变参数,进而计算形变量。在兰州新区的实验表明,与基于传统线性模型的SBAS-InSAR方法相比,该文方法在残余相位的建模精度提升了41.2%,与水准数据对比精度提升了20.1%。该研究可为黄土高填方工程长期变形分析与灾害预警提供数据支撑。

       

      Abstract: Land subsidence in loess-filled areas exhibits complex evolutionary mechanisms. Conventional linear models based on time-series interferometric synthetic aperture radar (InSAR) frequently face challenges in monitoring the nonlinear creep of loess. In this context, this study proposes an InSAR-based method that considers the nonlinear creep behavior. In this method, an adaptive thresholding technique based on tangent angle variations is used to detect and segmentally estimate the fill distribution and thickness. In the small baseline subset InSAR (SBAS-InSAR) framework, the constitutive equations for calculating the nonlinear creep of loess based on the fractional calculus theory are integrated with a differential interferometric phase model. The Chernobyl disaster optimizer (CDO) algorithm is employed to estimate creep parameters, followed by deformation calculation. Experiments carried out in the Lanzhou New Area suggest that, compared to the SBAS-InSAR method based on conventional linear models, the method developed in this study increased the residual-phase modeling accuracy by 41.2% and the degree of agreement with benchmark data by 20.1%. Therefore, this study can provide data support for analyzing long-term deformations and performing early warning of hazards for loess high-fill engineering.

       

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