| The unique geographical-hydrological environments of the Qinghai-Tibet Plateau(QTP)gives birth to the world's largest permafrost region.In recent years,under the background of continuous temperature rise and engineering activities,the frozen soil on the QTP shows a rapid degradation trend,which is mainly manifested in thickening of active layer and rising of permafrost temperature.The active layer is located above the permafrost and its periodic freeze-thaw cycles can cause the seasonal uplift and subsidence of the frozen soil.On the other hand,the economical construction and operation of the Qinghai-Tibet Railway(QTR)have changed the temperature and stress field of the frozen soil,thus causing geological disasters such as the railway subgrade subsiding and the permafrost thaw slumping.Therefore,it is of great scientific significance to carry out large-scale deformation monitoring of permafrost and along the QTP engineering corridor,investigation of permafrost distribution and estimation of active layer thickness for the environment,climate,disaster prevention and human engineering facilities on the QTP.However,the QTP has harsh natural environment,and the discontinuous permafrost has a more heterogeneous landscape,there are many defects in using conventional monitoring methods in permafrost research.The launch of multi-source SAR satellite and the rapid development of In SAR technology have provided abundant data sources and technical support for the study of the QTP.In this paper,to provide scientific basis and theoretical support for disaster protection and ecological protection of permafrost on the QTP,we collect Sentinel-1A,Terra SAR-X,and ALOS-2 PALSAR-2 data to carry out the deformation monitoring,permafrost distribution mapping and active layer thickness inversion research on the QTP.The main content and innovation work of this paper are as follows:(1)A Parallel Fast distributed scatterer-coherent scatters In SAR technique based on the supercomputer platform PFDS-CSINSAR(Parallel Fast Distribute scatterer-coherent scatters In SAR)is proposed to retrieve the annual mean deformation rate of the QTP.Due to there are few measurement points using CSIn SAR technology on the QTP and the processing efficiency of DSI technology(Distribute Scatterer interferometry)is low,we use Sentinel-1 images with the Interferometric Wide swath(IW)TOPS mode and a 250 km swath as the data source and improve the density of measurement points on the QTP by combining DS(Distribute Scatterer),then we propose a DSI parallel strategy to improve the computational efficiency of DSI algorithm so as to be more suitable for large-area deformation monitoring on the QTP.In the DSI processing process,a confidence interval method based on integral graph is proposed to extract statistically homogeneous pixels.Due to there are multiple scattering mechanisms in medium and low resolution SAR images and time-consuming problem of optimal phase calculation,the optimal phase of DS is estimated by singular value decomposition.The researches show that compared with CSIn SAR,PFDS-CSIn SAR greatly improves the quality of the interferograms and the density of the measurement points in the low-coherence permafrost region.The parallel DSI method reduces the DSI processing time which takes 35 h to 30 min using Sentinel-1(are multi-looked by factors of 20 and 4 along the range and azimuth directions),and improves the operating efficiency by nearly 60 times.The results of PFDS-CSIn SAR show that the annual mean deformation rate of the QTP is-56?56mm/yr from 2018 to 2019.The deformation of the QTP has a weak correlation with active layer thickness(ALT)and soil moisture content,and a strong correlation with the annual mean surface temperature.(2)An adaptive distributed scatterer technique based on seasonal deformation model and a new method of permafrost distribution mapping based on In SAR time-series deformation are proposed to implement the deformation monitoring of permafrost and mapping of deformation distribution along the QTR from Golmud to Lhasa.We use Sentinel-1 images with the Interferometric Wide swath(IW)TOPS mode and a 250 km swath and ERA5-Interim reanalysis daily air temperature as the data source.These problems exist in the process of using the PSI(Persistent Scatterer Interferometry)technology to monitor deformation along the QTR,such as there are few PS(Persistent Scatterer)and the applicability of deformation model.In this study,we combine DS with PS,and apply the seasonal deformation model based on the normalized freeze-thaw index to obtain the seasonal deformation of permafrost along the QTR.In the DSI process,the Shapiro-Wilk W test based on the covariance matrix of initial data blocks is proposed to extract statistically homogeneous pixels,and the initial covariance matrix is estimated by a robust M-Estimator method.In the optimal phase estimation step,Phase Linking method is used to solve the maximum likelihood estimation algorithm.To accelerate the iterative solving speed,the initial solution based on EMI(Eigendecomposition-based Maximum-likelihoodestimator)method is proposed as the initial condition of the iteration,thus improving the solving speed and accuracy of optimal phase.Based on the seasonal,time-series deformation and daily air temperature data,the freeze-thaw cycles in different areas along the QTR are analyzed.Finally,Savitzky-Golay filter algorithm is used to process In SAR time-series deformation and unsupervised ISODATA classification method is used to map permafrost distribution.The experimental results show that the seasonal deformation ranges from-70 to20mm/yr and the LOS deformation rate ranges from-40.0 to 20.0mm/yr during2017/03/16 to 20/03/24.The seasonal deformation range of the 10 km buffer zone along the QTR is-50?10mm/yr.The sections with large subsidence area are: from Golmud to Xidatan,from Budongquan to Hoh Xili,from Wudaolang to Beiluhe,from Fenghuoshan to Wuli,from Tuotuo River to Yanshiping,from Tanggula Mountain to Anduo,from Naqu to Dangxiong,and from Yangbajing to Lhasa.It has been proved that the correlation between In SAR measurement and leveling measurement at four sites are 0.93,0.91,0.89 and 0.83,respectively.In addition,based on the daily air temperature data and the time series deformation,it is found that the freeze-thaw cycles period of permafrost is different in different regions along the QTR.The permafrost region is classified into permafrost areas,seasonal frozen soil areas and degraded permafrost areas based on the classification results of In SAR time-series deformation.The classification results are basically consistent with the results of Zhao Lin's permafrost classification.(3)We analysis the freeze-thaw cycles deformation of permafrost in different geomorphic landscapes based on multi-source SAR data,and an inversion method of ALT based on multilayer soil moisture content and multilayer soil porosity data is proposed to implement the inversion of ALT in different geomorphic landscapes in Beiluhe basin.To solve the heterogeneity of permafrost distribution and complex geomorphic types in Beiluhe area,we use Sentinel-1,Terra SAR-X,ALOS-2 PALSAR-2 images as the data source and propose an ALT estimation method based on multilayer soil water content and multilayer soil porosity,then implement the NSBAS(New Small baseline Subsets)method based on the seasonal deformation model.Finally,the seasonal deformation and active layer thickness of different landscapes in Beiluhe area are obtained,and the deformation and ALT retrieved by different sensors are analyzed,so as to explore the applicability and difference of multi-source SAR data in the process of freeze-thaw cycles deformation and ALT inversion in permafrost region.The deformation results of multi-source SAR data show that the regions with the higher seasonal deformation values are mainly concentrated around thermal-melting lake,braided river plain,basin area,seasonal runoff area of glacier and floodplain area.The Sentinel-1 and ALOS-2 PALSAR-2 data show that the seasonal deformation trend is consistent,but the linear deformation rate is quite different.The In SAR results of Sentinel-1 and Terra SAR-X data show that seasonal deformation trends are consistent,exhibiting good correlations 0.78 and 0.84,respectively.The deformation results of the three sensors show that the seasonal deformation trend of six typical ground landscapes in Beiluhe area is consistent.The seasonal deformation in alpine meadow and floodplain areas is higher than that in alpine desert and bare areas.Combined with daily temperature data,soil moisture content and GPR data in Beiluhe area,it is found that the frozen soil deformation has important relationship with temperature,soil moisture content and ALT.The ALT retrieved by the three sensors ranges from 0.3 to 4.23 m,from 0.3 to 4.04 m,and from 0.3 to 4.54 m,respectively,and ALT of different landscapes is obviously different.By comparing ALT retrieved by the three sensors with the measured data of GPR,it can be found that the correlation of ALT retrieved by ALOS-2 PALSAR-2 data in different landscapes regions is the best,which is 0.87,0.78,0.89 and 0.80,respectively.The correlation between ALT of Terra SAR-X data and Sentinel-1 in floodplain area is poor,which is 0.59 and 0.63,respectively.The estimation method of ALT proposed in this paper provides an effective method for the inversion of active layer thickness on the QTP. |
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