Research And Application Of The Methods For Wide Area InSAR Deformation Monitoring

Large-scale,efficient and high-precision ground deformation measurement is an important data support for geological hazard detection and prevention,geo-parameter inversion and spatio-temporal evolution law analysis of displacements.The spaceborne Synthetic Aperture Radar(SAR)Interferometric(InSAR)plays an indispensable role in ground stability monitoring with its advantages of wide coverage,high spatial resolution and low-cost.With the development of SAR satellite and InSAR techniques,people have a growing demand for large-scale ground deformation measurement based on InSAR or multi-temporal InSAR(MT-InSAR),and promoted the huge application demand of wide-area InSAR technology.However,limited by the width of SAR frame and the accuracy and efficiency of computer solution,the current InSAR/MT-InSAR technology is mainly used to solve ground deformation in a small range by a single frame dataset.When the monitoring area requires multiple frames coverage and joint measurement,the InSAR datasets of multiple frames need to be solved one by one and then integrated to obtain wide-area results.InSAR,however,is a relative measurement technique with respect to a selected reference point.The consistency of the wide area results is great influenced by the stability of the reference datum of each frame in the wide area and the influence level of errors.Due to the difference of errors represented by atmospheric delay contained in each dataset,the accuracy of the independent results of each frame will vary due to the influence of spatio-temporal filtering model in the solution of deformation time series.In addition,the measurement of wide-area deformation requires massive InSAR datasets and lots of computing and storage resources.The improvement of computing efficiency is also an important issue in the wide-area InSAR ground deformation monitoring.Therefore,unification of the reference datum,spatio-temporal accuracy and calculation strategy are important bottleneck problems restricting the wide-area InSAR deformation measurement technology.In this thesis,we carry out a series of studies on wide-area InSAR technology for large-scale ground deformation monitoring.We systematically analyzed the main error sources existing in wide-area InSAR deformation measurement,improved the theory and method of wide-area InSAR high-precision deformation monitoring,and carried out the application demonstration in some typical scenarios,which will provide technical support for the wide-area InSAR technology in the field of ground deformation monitoring.The main contributions and innovations of this thesis are as follows:(1)This thesis presents a multi-frame deformation velocity splicing method for wide-area ground monitoring,based on the multi-frame InSAR dataset and block adjustment,to improve the spatial consistency and overall accuracy of wide-area InSAR deformation results.The existing wide-area InSAR measurement studies are simple to correct the deviation between the results of multiple frames results or rely on external GNSS data.Therefore,this study established the block adjustment correction model for the joint adjustment of the multi-frame InSAR deformation results in a wide area,based on the spatial topological relationship between the multi-frame InSAR data and the repeated observations in the overlapping regions between the adjacent frames in a wide area.The calculated deviation values are used to correct the differences between frames in a wide area,to obtain the wide-area InSAR deformation products with consistent spatial reference.To verify the proposed method,we select the Guangdong Province,China,about1.96×10~5km~2,to conduct the wide-area ground deformation monitoring.Compared with the original monitoring results,the accuracy of the corrected results is improved by about 19.2%.(2)This thesis presents a wide-area InSAR deformation velocity correction and fusion method by introducing GNSS data.By introducing GNSS data with dense spatial and temporal distribution in each frame,the field correction and the adjustment fusion of the overall results were carried out in each frame,which improved the error suppression effect of each frame and expanded the high precision monitoring technology of wide-area InSAR deformation.The existing methods of combining InSAR and GNSS data for wide-area ground deformation measurement have not considered enough the propagation and distribution characteristics of errors in the deformation results,with a poor universality.In this study,the low-frequency error correction model is constructed at a frame scale.The block adjustment correction model with GNSS observation is constructed at a wide-area scale.The low-frequency error and reference error in the multi-frame InSAR results are corrected.The deformation products with the same absolute reference in a wide-area space are obtained.The proposed method is experimentally verified in the wide-area InSAR deformation monitoring in the northwest US(NWUS).The whole-area deformation products from 2019 to 2021 in the NWUS are obtained.Compared with the previous method,the accuracy of GNSS data introduced for secondary correction is improved by 18.5%.(3)This thesis presents a wide-area InSAR variable scale deformation detection strategy,to reduce the implementation cost and improve the efficiency of wide-area InSAR deformation detection by introducing the MT-InSAR fast solution method and an adaptive recognition algorithm.Most of the current wide-area InSAR monitoring strategies have fully calculated the temporal deformation of the ground.Even if the spatial resolution of the monitoring results is adjusted,there are still deficiencies such as low efficiency,large amount of repeated calculation and redundancy of results.The proposed strategy combines the Stacking technology for fast ground deformation rate calculation,the advanced TS-InSAR technologies,and the wide-area InSAR deformation monitoring methods mentioned above,for obtaining fine deformation time series.It adopts an adaptive recognition algorithm to identify the spatial distribution and area of deformation regions(regions of interest,ROI)in the wide study area and uses a novel wide-area deformation products organization structure to generate the variable-scale deformation products.The Turpan-Hami basin in western China is selected as the wide study area(277,000 km~2)to verify the proposed WAVS-InSAR strategy.The WAVS-InSAR strategy will be helpful for the InSAR deformation monitoring on national/regional scale and promote the engineering application of InSAR technology.(4)This thesis obtains the first long-term and large-scale InSAR deformations of the oasis agricultural area in the southern Junggar basin(JSOAA)and the Hutubi underground gas storage(HUGS).Combined with the geological mechanism in the deformation regions,the geological model of the most significant ground deformation caused by groundwater overextraction and the injection and production of HUGS are constructed,and the health of the aquafer and the operation status of HUGS are inverted and evaluated.JSOAA is an important agricultural and industrial production base in western China,but water scarcity.The overextraction of groundwater by agricultural irrigation causes the aquifer in this area to be in a state of net loss for a long time,leading to ground subsidence.The wide-area InSAR technology is used to process all ALOS-1/PALSAR and Sentinel-1 data in the JSOAA,and obtain the wide-area long-term deformation of this region for the first time.The correlation between ground subsidence caused by groundwater overextraction and geographical location,hydrogeological conditions and human activities are revealed in JSOAA.An analytical model is built to evaluate the volume strain and the total groundwater deficit of the aquifer during 2007-2020.We model and analyze the HUGS,currently the largest UGS in China,and traceback the long-term deformation before and after the transformation as a UGS,and introduces a composite dislocations model to model the injection/extraction related ground deformation in HUGS.