基于雷达遥感对地观测技术的软土地区公路沉降监测方法

Monitoring method for subsidence of highways in soft soil areas based on radar remote sensing earth observation technique

为克服传统公路沉降监测方法需耗费大量人力物力且监测范围有限的问题,旨在提出一种基于雷达遥感对地观测技术(In SAR)的软土地区公路沉降自动化、大范围监测方法。考虑软土沉降特征,将非线性黏弹塑性四元件组合流变模型引入InSAR形变建模,提出软土地区公路沉降物理模型,并建立InSAR时序相位方程组,估计沉降未知参数,以计算获取公路大范围面状沉降结果。通过模拟数据和广东伦桂路水准实测数据验证了该方法的可行性和可靠性。结果表明:与软土In SAR线性模型计算方法相比,该方法精度提升24%;与传统地面水准实测方法相比,该方法获取的软土地区公路沉降均方根误差为±5.6mm,相对精度为5%,且趋势与水准实测结果一致。将该方法应用于湖南岳阳湖区公路大范围沉降监测,获取了该区1.5 a的时序沉降结果;该区域公路沉降呈现先快后慢的趋势,累积最大沉降达46mm,沿湖区沉降明显大于内陆区。可为软土地区公路沉降早期识别和养护管理提供依据。

A large-scale automatic surface monitoring method for highways built in soft soil areas based on the InSAR technique is proposed to overcome the deficiencies of labor-consuming and unavailability of large-scale deformation by the traditional monitoring method for ground subsidence of highways.Considering the deformation characteristics of soft soils,a nonlinear viscoelastic-plastic four-component combined rheological model is introduced into the InSAR deformation modeling.Then the physical soft soil highway subsidence model is proposed and the time-series InSAR functions are established.The parameters for subsidence are estimated to calculate the results of the large-scale surface deformation areas of highways.The simulated and field tests on a segment of Lungui Road in Guangdong Province are carried out.Compared to that of the traditional linear model,the modeling accuracy of the proposed method has an improvement of 24%.The RMSE for Lungui Road is estimated as±5.6 mm,with a relative accuracy of 5%and a good consistency with its deformation tendency.A case study of a highway near Dongting Lake in Yueyang,Hunan Province is carried out to verify the capacity,and the 1.5-year time-series settlement results are obtained,with the subsidence rate following a fast-to-slow nonlinear capacity.The results show that the subsidence near Dongting Lake is significantly higher than that in the inland area,with the maximum subsidence accumulated to 46 mm.The proposed method may provide a reference for early subsidence detection and maintenance management of soft soil highways.