Multi-dimensional, long-term time series displacement monitoring is crucial for generating early warnings for active landslides and for mitigating geohazards. The synthetic aperture radar(SAR) interferometry method ha...Multi-dimensional, long-term time series displacement monitoring is crucial for generating early warnings for active landslides and for mitigating geohazards. The synthetic aperture radar(SAR) interferometry method has been widely applied to achieve small-gradient landslide displacement monitoring;however, measuring the landslide displacement with a steep gradient has posed certain challenges. In comparison, the SAR offset tracking method is a powerful tool for mapping large-gradient landslide displacement in both the slant-range and azimuth directions. Nevertheless, there are some limitations in the existing SAR offset tracking approaches:(i) the measurement accuracy is greatly reduced by the extreme topography relief in high mountain areas,(ii) a fixed matching window from expert experience is usually adopted in the calculation of cross-correlation,(iii) estimating the long-term displacements between the SAR images from cross-platforms and with longer spatiotemporal baselines is a challenging task, and(iv) it is difficult to calculate the three-dimensional(3D) landslide displacements using a single SAR dataset.Additionally, only a few studies have focused on how to realize early warning of landslide deformation using SAR measurements.To address these issues, this paper presents an improved cross-platform SAR offset tracking method, which can not only estimate high-precision landslide displacements in two and three dimensions but also calculate long-term time series displacements over a decade using cross-platform SAR offset tracking measurements. Initially, we optimize the traditional SAR offset tracking workflow to estimate high-precision ground displacements, in which three improvements are highlighted:(i) an“ortho-rectification” operation is applied to restrain the effect of topography relief,(ii) an “adaptive matching window” is adopted in the cross-correlation computation, and(iii) a new strategy is proposed to combine all the possible offset pairs and optimally design the displacement inversion network based on the “optimization theory” of geodetic inversion. Next, robust mathematical equations are built to estimate the two-dimensional(2D) and 3D long-term time series landslide displacements using cross-platform SAR observations. The M-estimator is introduced into the 2D displacement inversion equation to restrain the outliers, and the total least squares criterion is adopted to estimate the 3D displacements considering the random errors in both the design matrix and observations. We take the Laojingbian landslide, Wudongde Reservoir Area(China), as an example to demonstrate the proposed method using ALOS/PALSAR-1 and ALOS/PALSAR-2 images. The results reveal that the proposed method significantly outperforms traditional methods. We also retrieve the movement direction of each pixel of the Laojingbian landslide using the proposed method, thus allowing us to understand the fine-scale landslide kinematics. Finally, we capture and analyze the acceleration characteristics of the landslide, perform an early warning of hazard, and forecast the future displacement evolution based on the 3D displacement time series coupled with the physical models of the rocks.展开更多
Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understa...Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks.In this paper,the main outcomes relevant to the joint European Space Agency(ESA)and the Chinese Ministry of Science and Technology(MOST)Dragon-5 initiative cooperation project ID 59,339“Earth observation for seismic hazard assessment and landslide early warning system”are reported.The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks,detect potential landslides in wide regions,and demonstrate EO-based landslide early warning system over selected landslides.This work only focuses on the landslide hazard content of the project,and thus,in order to achieve these objectives,the following tasks were developed up to now:a)a procedure for phase unwrapping errors and tropospheric delay correction;b)an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements;c)the application of polarimetric SAR interferometry(PolInSAR)to increase the number and quality of monitoring points in landslide-prone areas;d)the semiautomatic mapping and preliminary classification of active displacement areas on wide regions;e)the modeling and identification of landslides in order to identify triggering factors or predict future displacements;and f)the application of an InSAR-based landslide early warning system on a selected site.The achieved results,which mainly focus on specific sensitive regions,provide essential assets for planning present and future scientific activities devoted to identifying,mapping,characterizing,monitoring and predicting landslides,as well as for the implementation of early warning systems.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41874005 and 41929001)the Fundamental Research Funds for the Central Universities,CHD (Grant Nos. 300102269712 and 300102269303)+1 种基金by the China Geological Survey Projects (Grant Nos. DD20190637 and DD20190647)supported by a Chinese Scholarship Council studentship awarded to Xiaojie Liu (Grant No. 202006560031)。
文摘Multi-dimensional, long-term time series displacement monitoring is crucial for generating early warnings for active landslides and for mitigating geohazards. The synthetic aperture radar(SAR) interferometry method has been widely applied to achieve small-gradient landslide displacement monitoring;however, measuring the landslide displacement with a steep gradient has posed certain challenges. In comparison, the SAR offset tracking method is a powerful tool for mapping large-gradient landslide displacement in both the slant-range and azimuth directions. Nevertheless, there are some limitations in the existing SAR offset tracking approaches:(i) the measurement accuracy is greatly reduced by the extreme topography relief in high mountain areas,(ii) a fixed matching window from expert experience is usually adopted in the calculation of cross-correlation,(iii) estimating the long-term displacements between the SAR images from cross-platforms and with longer spatiotemporal baselines is a challenging task, and(iv) it is difficult to calculate the three-dimensional(3D) landslide displacements using a single SAR dataset.Additionally, only a few studies have focused on how to realize early warning of landslide deformation using SAR measurements.To address these issues, this paper presents an improved cross-platform SAR offset tracking method, which can not only estimate high-precision landslide displacements in two and three dimensions but also calculate long-term time series displacements over a decade using cross-platform SAR offset tracking measurements. Initially, we optimize the traditional SAR offset tracking workflow to estimate high-precision ground displacements, in which three improvements are highlighted:(i) an“ortho-rectification” operation is applied to restrain the effect of topography relief,(ii) an “adaptive matching window” is adopted in the cross-correlation computation, and(iii) a new strategy is proposed to combine all the possible offset pairs and optimally design the displacement inversion network based on the “optimization theory” of geodetic inversion. Next, robust mathematical equations are built to estimate the two-dimensional(2D) and 3D long-term time series landslide displacements using cross-platform SAR observations. The M-estimator is introduced into the 2D displacement inversion equation to restrain the outliers, and the total least squares criterion is adopted to estimate the 3D displacements considering the random errors in both the design matrix and observations. We take the Laojingbian landslide, Wudongde Reservoir Area(China), as an example to demonstrate the proposed method using ALOS/PALSAR-1 and ALOS/PALSAR-2 images. The results reveal that the proposed method significantly outperforms traditional methods. We also retrieve the movement direction of each pixel of the Laojingbian landslide using the proposed method, thus allowing us to understand the fine-scale landslide kinematics. Finally, we capture and analyze the acceleration characteristics of the landslide, perform an early warning of hazard, and forecast the future displacement evolution based on the 3D displacement time series coupled with the physical models of the rocks.
基金supported by the ESA-MOST China DRAGON-5 project with ref.59339,by the Spanish Ministry of Science and Innovation,the State Agency of Research(AEI)the European Funds for Regional Development under grant[grant number PID2020-117303GB-C22]+5 种基金by the Conselleria de Innovación,Universidades,Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335by the Natural Science Foundation of China[grant numbers 41874005 and 41929001]the Fundamental Research Funds for the Central University[grant numbers 300102269712 and 300102269303]China Geological Survey Project[grant numbers DD20190637 and DD20190647]Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref.[grant number 202006560031][grant number 202004180062],respectively.
文摘Landslides are destructive geohazards to people and infrastructure,resulting in hundreds of deaths and billions of dollars of damage every year.Therefore,mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks.In this paper,the main outcomes relevant to the joint European Space Agency(ESA)and the Chinese Ministry of Science and Technology(MOST)Dragon-5 initiative cooperation project ID 59,339“Earth observation for seismic hazard assessment and landslide early warning system”are reported.The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks,detect potential landslides in wide regions,and demonstrate EO-based landslide early warning system over selected landslides.This work only focuses on the landslide hazard content of the project,and thus,in order to achieve these objectives,the following tasks were developed up to now:a)a procedure for phase unwrapping errors and tropospheric delay correction;b)an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements;c)the application of polarimetric SAR interferometry(PolInSAR)to increase the number and quality of monitoring points in landslide-prone areas;d)the semiautomatic mapping and preliminary classification of active displacement areas on wide regions;e)the modeling and identification of landslides in order to identify triggering factors or predict future displacements;and f)the application of an InSAR-based landslide early warning system on a selected site.The achieved results,which mainly focus on specific sensitive regions,provide essential assets for planning present and future scientific activities devoted to identifying,mapping,characterizing,monitoring and predicting landslides,as well as for the implementation of early warning systems.
