Study On The Method And Application Of Time-series InSAR Subsidence Monitoring By Fusing Highly Coherent And Distributed Targets

In recent years,ground subsidence has been a major disaster in terms of the damage to people’s lives and property,and it has gradually become a very dangerous geological hazard.Enhancing the monitoring of ground subsidence and taking timely management measures are effective means to prevent and manage this type of geological disaster.Synthetic Aperture Radar Interferometry(In SAR)technology has shown great potential for all types of ground subsidence monitoring due to its all-weather,contactless,wide-area ground observation capability.However,in practical application,due to the influence of complex environment,such as: low vegetation cover,narrow spatial distribution,etc.,resulting in the problem of sparse point density of the time-series In SAR technology,which affects the In SAR data processing leading to low accuracy of subsidence monitoring,and at the same time,cannot provide more detailed ground subsidence information for geohazard monitoring and management.This limits the further engineering application of the technology.Therefore,based on the study of the point selection method of the time-series In SAR technology,this thesis proposes the fusion method of highly coherent point targets(PS and SDFP points)and distributed targets(DS points),aiming to make full use of the stable targets that maintain stable scattering characteristics in the long time series to improve the density of ground settlement monitoring points,to solve the problem of sparse monitoring points in the practical application of the traditional time-series In SAR technology,and to enhance its ground settlement monitoring capability.The main findings and results of the research are as follows:(1)To address the problem of insufficient density of highly coherent targets acquired by conventional time-series In SAR,the thesis taking into account the intensity and phase stability of the scattering characteristics of the ground target,proposes a fusion method of PS,SDFP and DS points based on the weighted average of coherent target signal-to-noise ratio.This method considers the signal-to-noise ratio of PS points and SDFP points,obtaining the PS/SDFP point phase values according to SNR weighted average,further obtaining the PS/SDFP/DS phase values by integrating the acquired PS/SDFP points and DS points in the same way.The In SAR time series high coherence points were then ac-quired,and thus a time-series In SAR ground subsidence monitoring data processing process was constructed to fuse the highly coherent and distributed targets.(2)The thesis uses the method proposed in this paper to solve the problem of sparse point targets due to vegetation cover and large subsidence magnitude of surface features.The effectiveness of the proposed method is verified by comparing the point density,subsidence rate and correlation obtained with the traditional time-series In SAR(PS-In SAR,SBAS-In SAR)technique for ground subsidence monitoring in a mining area in Heze.The results show that the ground subsidence monitoring results obtained by the proposed method have improved in terms of the number and spatial distribution density of monitoring points and the range of values of subsidence results compared with the traditional time-series In SAR technique.(3)To address the problem of sparse point targets caused by the narrow spatial distribution of linear features,the thesis uses the proposed method and the traditional time-series In SAR technique to monitor ground subsidence in the road network and rail transit in Jinan,and analyses the differences in the number of obtained highly coherent points and subsidence results in different classes of roads.The results show that the density of point targets acquired by the proposed method within the road network of Jinan increases significantly,especially for suburban sections of high-speed roads and urban expressways,improving the problem of uneven distribution of subsidence results in narrow road areas and increasing the completeness of coverage of road network deformation results.