Monitoring The Landslides Deformation With MT-InSAR Technique

Geological disasters occur frequently in China,causing countless casualties and economic losses every year.According to statistics,a total of 4772 geological disasters occurred nationwide in 2021,resulting in 80 deaths and 11 missing,with a direct economic loss of 3.2billion Yuan.The landslide is one of common,heaviest,and most widely distributed geological disasters,deeply affecting various provinces,cities,and regions in China.Reducing and avoiding the harm of landslide disasters,and strengthening the construction of landslide monitoring,warning,and prediction systems,is one of the focuses of research in China.Deformation monitoring on landslides can obtain the time series from stability to instability,providing certain data support for landslide prediction and warning.The MT-In SAR technology can avoid spatiotemporal decorrelation and reduce atmospheric influence,with the advantages of all-day,all-weather,high-precision,and large-scale surface measurement.It has been widely used in long-term landslide deformation monitoring.However,the lack of highly coherent pointy targets the influence of serious atmospheric errors still exists.At 00:20 on October 21,2017,a landslide disaster occurred due to continuous rainfall,in Guang’an Village,Dahe Township,Wuxi County,Chongqing,with a landslide body about 400m long and a total volume of about 6 million m~3.It resulted in one household with 9 people buried and missing,more than 160 people urgently relocated,26 houses and 62 rooms collapsed,and a direct economic loss of more than 5 million Yuan.The Guang’an Village landslide is a large high rocky landslide,with high danger and wide threats influence.Once the landslide is re-activated,it will directly block the river for about 500m and form a barrier lake,directly threatening the lives and property of residents along the upstream and downstream.Thus,this paper generated mean deformation velocity and deformation time-series of the Guang’an Village landslide,analyzed the deformation motion characteristics and conducts collapse volume modeling to provide data support for disaster prevention and reduction of secondary landslides.The main research achievements of this paper are followed:(1)Compare and analyze the effectiveness of the four atmospheric error correction methods(the spatiotemporal filtering method,first-order and quadratic polynomial height fitting method,and external data ERA5 model correction method)with SBAS-In SAR technology.The results indicate that the quadratic polynomial elevation fitting correction method is the optimal atmospheric error correction method in the study area of this paper.It provide a reference for the selection of atmospheric error correction methods for In SAR monitoring research in mountainous areas with large surface undulation,large deformation magnitude,and small coverage area.(2)An enhanced Sta MPS-SBAS technique which operates on multi-look differential interferograms was proposed and applied to the time-series deformation monitoring of the Guang’an Village landslide.As a result,a total of 14,967 MPs were acquired,which was 51.8%more than the number of MPs acquired with the traditional Sta MPS-SBAS technique,covering more than 95%of the landslide area.(3)Long-term deformation monitoring was carried out for the Guang’an Village landslide and its surrounding dangerous areas.The results show that:(1)the deformation of the Guang’an Village landslide is distributed in a‘human’shape in space,including SA,TA,DA,and PSA3.The maximum subsidence rate reaches-89.4mm/yr,and the maximum cumulative subsidence is-331.2mm.(2)the whole observation period was divided into three stages in terms of a year,S1:before December 2018;S2:2019.01-2019.12;S3:After 2020.01.According to mean deformation velocity corresponding to the three stages and the time series analysis of the four active deformation areas,the majority of the Guang’an Village landslide has tended to be stable,but PSA3 is still in accelerated deformation.There is the possibility of a secondary landslide in PSA3.(3)the correlation coefficient,R~2=0.88,between the deformation of the Guang’an Village landslide and the rainfall.Once the strong rainfall causes accelerated deformation of PSA3 and increases the pressure of the anti-slip zone,it will lead to a secondary landslide.(4)a total of 69 historical landslide samples similar to the Guang’an Village landslide were used to model the relationship between the area and volume of the single landslide.The collapse volume of PSA3 calculated by this model is 5×106m3.