scholarly journals Radar Interferometry Time Series to Investigate Deformation of Soft Clay Subgrade Settlement—A Case Study of Lungui Highway, China

2019 ◽  
Vol 11 (4) ◽  
pp. 429 ◽  
Author(s):  
Xuemin Xing ◽  
Hsing-Chung Chang ◽  
Lifu Chen ◽  
Junhui Zhang ◽  
Zhihui Yuan ◽  
...  
Keyword(s):  
Time Series ◽  
Ground Deformation ◽  
Soft Clay ◽  
Velocity Model ◽  
Radar Interferometry ◽  
Suitable Model ◽  
Seasonal Model ◽  
Soft Clay Subgrade ◽  
Sbas Insar ◽  
Deformation Models

Monitoring surface movement near highways over soft clay subgrades is fundamental for understanding the dynamics of the settlement process and preventing hazards. Earlier studies have demonstrated the accuracy and cost-effectiveness of using time series radar interferometry (InSAR) technique to measure the ground deformation. However, the accuracy of the advanced differential InSAR techniques, including short baseline subset (SBAS) InSAR, is limited by the temporal deformation models used. In this study, a comparison of four widely used time series deformation models in InSAR, namely Multi Velocity Model (MVM), Permanent Velocity Model (PVM), Seasonal Model (SM) and Cubic Polynomial Model (CPM), was conducted to measure the long-term ground deformation after the construction of road embankment over soft clay subgrade. SBAS-InSAR technique with TerraSAR-X satellite imagery were conducted to generate the time series deformation data over the studied highway. In the experiments, three accuracy indices were applied to show the residual phase, mean temporal coherence and the RMS of high-pass deformation, respectively. In addition, the derived time series deformation maps of the highway based on the four selected models and 17 TerraSAR-X images acquired from June 2014 to November 2015 were compared. The leveling data was also used to validate the experimental results. Our results suggested the Seasonal Model is the most suitable model for the selected study site. Consequently, we analyzed two bridges in detail and three single points distributed near the highway. Compared with the ground leveling deformation measurements and results of other models, SM showed better consistency, with the accuracy of deformation to be ±7 mm.

scholarly journals An Improved Time-Series Model Considering Rheological Parameters for Surface Deformation Monitoring of Soft Clay Subgrade

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3073 ◽  
Author(s):  
Xing ◽  
Chen ◽  
Yuan ◽  
Shi
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Soft Clay ◽  
Deformation Monitoring ◽  
Rheological Parameters ◽  
Deformation Model ◽  
Rheological Parameter ◽  
Functional Relationships ◽  
Soft Clay Subgrade ◽  
Deformation Models

Building deformation models consistent with reality is a crucial step for time-series deformation monitoring. Most deformation models are empirical mathematical models, lacking consideration of the physical mechanisms of observed objects. In this study, we propose an improved time-series deformation model considering rheological parameters (viscosity and elasticity) based on the Kelvin model. The functional relationships between the rheological parameters and deformation along the Synthetic Aperture Radar ( SAR) line of sight are constructed, and a method for rheological parameter estimation is provided. To assess the feasibility and accuracy of the presented model, both simulated and real deformation data over a stretch of the Lungui highway (built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. With the proposed deformation model, the unknown rheological parameters over all the high coherence points are obtained and the deformation time-series are generated. The high-pass (HP) deformation component and external leveling ground measurements are utilized to assess the modeling accuracy. The results show that the root mean square of the residual deformation is ±1.6 mm, whereas that of the ground leveling measurements is ±5.0 mm, indicating an improvement in the proposed model by 53%, and 34% compared to the pure linear velocity model. The results indicate the reliability of the presented model for the application of deformation monitoring of soft clay highways. The estimated rheological parameters can be provided as a reference index for the interpretation of long-term highway deformation and the stability control of subgrade construction engineering.

scholarly journals Ground Subsidence Investigation in Fuoshan, China, Based on SBAS-InSAR Technology with TerraSAR-X Images

2019 ◽  
Vol 9 (10) ◽  
pp. 2038 ◽  
Author(s):  
Yikai Zhu ◽  
Xuemin Xing ◽  
Lifu Chen ◽  
Zhihui Yuan ◽  
Pingying Tang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Soft Clay ◽  
Ground Surface ◽  
Ground Subsidence ◽  
Maintenance Cost ◽  
Deformation Model ◽  
Geotechnical Characteristics ◽  
Soft Clay Subgrade ◽  
Sbas Insar

Highways built on soft clay subgrade are more prone to subsidence due to the geotechnical characteristics of soft clay. Monitoring ground movements in this area is significant for understanding the deformation dynamics and reducing maintenance cost as well. In this paper, small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technique is exploited to obtain and investigate the time series ground surface deformation after the construction of a road embankment over soft clay settlement. Considering the important effect of temporal deformation models on the final accuracy of estimated deformation, both the linear velocity model and seasonal deformation model are utilized to conduct the comparative investigation of deformation time series. Two highways in Fuoshan, China—G1501 Guangzhou Belt Highway and Lungui Highway—were selected as the test area. Thirteen TerraSAR-X images acquired from October 2014 to November 2015 were analyzed. Comparative study based on two groups of analyses generated from the two models for both highways were conducted. Consequently, several feature points distributed near the two highways were analyzed in detail to understand the temporal evolution of the settlement. In order to evaluate the reliability of our measurements, the residual phase was analyzed to assess the modelling accuracy of the two models. In addition, leveling data were also used to validate the experimental results. Our measurements suggest that the seasonal model is more suitable for the test highways, with an accuracy of ±3 mm with respect to the leveling results.

scholarly journals INVESTIGATION ON INSAR TIME SERIES DEFORMATION MODEL CONSIDERING RHEOLOGICAL PARAMETERS FOR SOFT CLAY SUBGRADE MONITORING

2018 ◽  
Vol XLII-3 ◽  
pp. 1977-1982 ◽  
Author(s):  
X. Xing ◽  
Z. Yuan ◽  
L. F. Chen ◽  
X. Y. Yu ◽  
L. Xiao
Keyword(s):  
Time Series ◽  
Soft Clay ◽  
Stability Control ◽  
Deformation Monitoring ◽  
Rheological Parameters ◽  
Deformation Model ◽  
Unknown Parameters ◽  
New Model ◽  
Soft Clay Subgrade ◽  
Deformation Models

The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

scholarly journals Countrywide Monitoring of Ground Deformation Using InSAR Time Series: A Case Study from Qatar

2021 ◽  
Vol 13 (4) ◽  
pp. 702
Author(s):  
Mustafa Kemal Emil ◽  
Mohamed Sultan ◽  
Khaled Alakhras ◽  
Guzalay Sataer ◽  
Sabreen Gozi ◽  
...  
Keyword(s):  
Time Series ◽  
Arabian Peninsula ◽  
Ground Deformation ◽  
Anthropogenic Activities ◽  
Urban Centers ◽  
Alos Palsar ◽  
Groundwater Levels ◽  
Temporal Correlations ◽  
Time Series Approach ◽  
Sbas Insar

Over the past few decades the country of Qatar has been one of the fastest growing economies in the Middle East; it has witnessed a rapid increase in its population, growth of its urban centers, and development of its natural resources. These anthropogenic activities compounded with natural forcings (e.g., climate change) will most likely introduce environmental effects that should be assessed. In this manuscript, we identify and assess one of these effects, namely, ground deformation over the entire country of Qatar. We use the Small Baseline Subset (SBAS) InSAR time series approach in conjunction with ALOS Palsar-1 (January 2007 to March 2011) and Sentinel-1 (March 2017 to December 2019) synthetic aperture radar (SAR) datasets to assess ground deformation and conduct spatial and temporal correlations between the observed deformation with relevant datasets to identify the controlling factors. The findings indicate: (1) the deformation products revealed areas of subsidence and uplift with high vertical velocities of up to 35 mm/yr; (2) the deformation rates were consistent with those extracted from the continuously operating reference GPS stations of Qatar; (3) many inland and coastal sabkhas (salt flats) showed evidence for uplift (up to 35 mm/yr) due to the continuous evaporation of the saline waters within the sabkhas and the deposition of the evaporites in the surficial and near-surficial sabkha sediments; (4) the increased precipitation during Sentinel-1 period compared to the ALOS Palsar-1 period led to a rise in groundwater levels and an increase in the areas occupied by surface water within the sabkhas, which in turn increased the rate of deposition of the evaporitic sediments; (5) high subsidence rates (up to 14 mm/yr) were detected over landfills and dumpsites, caused by mechanical compaction and biochemical processes; and (6) the deformation rates over areas surrounding known sinkhole locations were low (+/−2 mm/yr). We suggest that this study can pave the way to similar countrywide studies over the remaining Arabian Peninsula countries and to the development of a ground motion monitoring system for the entire Arabian Peninsula.

scholarly journals An Analysis of Vertical Crustal Movements along the European Coast from Satellite Altimetry, Tide Gauge, GNSS and Radar Interferometry

2021 ◽  
Vol 13 (11) ◽  
pp. 2173
Author(s):  
Kamil Kowalczyk ◽  
Katarzyna Pajak ◽  
Beata Wieczorek ◽  
Bartosz Naumowicz
Keyword(s):  
Time Series ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Measurement Techniques ◽  
Radar Interferometry ◽  
Vertical Movements ◽  
Persistent Scatterer ◽  
Gnss Time Series ◽  
Vertical Crustal Movements ◽  
European Coast

The main aim of the article was to analyse the actual accuracy of determining the vertical movements of the Earth’s crust (VMEC) based on time series made of four measurement techniques: satellite altimetry (SA), tide gauges (TG), fixed GNSS stations and radar interferometry. A relatively new issue is the use of the persistent scatterer InSAR (PSInSAR) time series to determine VMEC. To compare the PSInSAR results with GNSS, an innovative procedure was developed: the workflow of determining the value of VMEC velocities in GNSS stations based on InSAR data. In our article, we have compiled 110 interferograms for ascending satellites and 111 interferograms for descending satellites along the European coast for each of the selected 27 GNSS stations, which is over 5000 interferograms. This allowed us to create time series of unprecedented time, very similar to the time resolution of time series from GNSS stations. As a result, we found that the obtained accuracies of the VMEC determined from the PSInSAR are similar to those obtained from the GNSS time series. We have shown that the VMEC around GNSS stations determined by other techniques are not the same.

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