Study On Seasonal Deformation Monitoring Of Transportation Infrastructure With PS Series Integrating ESMD And STL

With the rapid development of society and economy,a large number of roads,buildings,high-speed railroads,bridges and other infrastructures have been built in China.However,ground settlement problems caused by groundwater overdraft and underground space development,etc.,as well as uneven distribution of water resources and extreme weather problems caused by global climate change,have seriously affected the smoothness of transportation routes.In addition,the increasing operating hours and environmental loads can also undermine the stability of transportation infrastructure structures,which may cause safety hazards or even directly threaten their safe operation.Therefore,the operational safety of urban transportation infrastructures,as an important practical issue,has drawn increasing attention from the fields of public safety,earth observation and civil engineering,and there is an urgent need for a scientific and efficient technical means to finely monitor them and provide technical guarantee for timely detection of safety hazards and ensure their safe operation.The multi-temporal synthetic aperture radar interferometry(MT-InSAR)technology,with its superiority of high spatial and temporal resolution,non-contact measurement,data reusability and all-weather monitoring,makes it possible to normalize and refine the monitoring of large linear features,and is increasingly applied in the field of deformation monitoring of important infrastructure transportation facilities.However,this technique mostly uses linear deformation function model in estimating nonlinear deformation,which can directly lead to the misestimation of nonlinear deformation information.Currently,related research has been conducted to improve the shortcomings of the traditional MT-InSAR method in estimating nonlinear deformation information by introducing a nonlinear function model for fitting in the deformation solution process.However,prior knowledge is required for introducing nonlinear functions,incorrect introduction of them may cause overfitting and function coupling,as well as misestimation of deformation parameters due to the high correlation between nonlinear and linear functions.Therefore,in order to tackle the aforementioned problems,the main researches of this paper are as follows:(1)Obtaining surface deformation information along typical regional transportation infrastructure.To address the practical problem of deformation of transportation infrastructure under the influence of surface settlement and by environmental and human factors during the operation process,PS-InSAR and SBAS-InSAR techniques were used to monitor the surface deformation of the integrated transportation network at Daxing International Airport in Daxing,Beijing for a long time series using Sentinel-1A/B data and Terra SAR-X data.The surface deformation results at different scales along the main traffic routes of Daxing Airport were obtained from 2017 to 2022.Sentinel-1A/B monitoring results show that there are several obvious surface deformation areas near Daxing International Airport with the highest average annual deformation rate of-79.34 mm/yr during 2017 to2021.Terra SAR-X images The refined monitoring results show that from 2021 to 2022,the average annual deformation rate at the intersection of Beijing-Xiong Intercity Railway,Lang Zhuo Intercity Railway and Capital Ring Road Expressway on the south side of Daxing Airport exceeds-20mm/yr,and the accumulated deformation rate can be as high as-70mm;the intersection of Beijing-Shanghai High-speed Railway and Beijing-Taiwan Expressway on the southwest side of Anding Town,the intersection of New Airport North Expressway and Daxing Airport Expressway in Lixian Town and the northeast side of Daxing Airport have an average deformation rate of about-20mm/yr.The deformation results obtained from the lowand medium-resolution Sentinel-1A/B data and the high-resolution Terra SAR-X data are consistent in terms of deformation magnitude and spatial distribution,and are in good agreement with the existing research results.(2)Analyzing the spatial and temporal characteristics of traffic infrastructure deformation patterns and the main deformation influencing factors.Based on the long time series MT-InSAR deformation monitoring results of Daxing Airport integrated traffic network,we analyze the spatial and temporal deformation characteristics and laws of Daxing Airport integrated traffic network by using various GIS spatial analysis techniques,and analyze the causes of deformation by studying the hydrological,geological and climatic related data in the area.The results show that multiple areas of deformation exist in the primary transportation routes of Daxing Airport.Among them,the maximum annual average deformation rate of the airport northern highway is as high as-47.19mm/yr,the deformation rate of the south side of the south bridge of the Beijing-Taiwan highway is-51.36mm/yr,and the deformation rate of the Beijing-Kowloon railroad,Lang Zhuo inter-city railroad,Beijing-Xiong inter-city railroad and Da Guang highway is as high as-58.43mm/yr,which is located near Yongding River.Based on the overall deformation pattern of the traffic network,the results of high-resolution Terra SAR-X reveal that the structural material and construction form of traffic lines affect the deformation of traffic lines to a certain extent.Finally,using GIS technology to combine the data of water systems,traffic lines,residential buildings and fracture zones,we found that the two main factors affecting the deformation are water systems and traffic lines,and the temperature and precipitation changes have a strong correlation with the deformation of bridges,roads and other traffic facilities in time.(3)Studying the seasonal deformation characteristics of basic transportation facilities.To address the problem that the seasonal fluctuations of the time-series deformation results of Daxing Airport and the surrounding major linear projects are easily affected by the ambient temperature and rainfall,two signal decomposition algorithms,ESMD and STL,are used to extract the seasonal physical signals to quantify and analyze the contributions of rainfall,groundwater and temperature to the seasonality of the time-series in the environmental load.The experimental results show that the ESMD algorithm can be obtained that there are obvious nonlinear fluctuations in traffic facility deformation with fluctuation periods of about120 and 360 days.Based on the seasonal fluctuation period provided by the ESMD algorithm,the seasonal trend decomposition of the three main IMFs at Q1 and Q2 using the STL algorithm achieves the extraction of a single seasonal variation from the complex seasonal factors.The correlations of each modal seasonal component obtained by decomposition using the STL algorithm were calculated with rainfall,air temperature and groundwater data,and it was found that the characteristic point IMF3 modal seasonal component had the highest correlation with air temperature and precipitation changes,while groundwater changes had the strongest correlation with IMF2 modal seasonal component.The joint analysis of the results of the IMF3 modal seasonal component with air temperature using the Q2 point reveals that the effect of air temperature on the viaduct deformation has a delayed effect,and the viaduct will undergo a certain degree of thermal expansion or contraction when the temperature changes.