scholarly journals Deriving Centimeter-Level Coseismic Deformation and Fault Geometries of Small-To-Moderate Earthquakes From Time-Series Sentinel-1 SAR Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Heng Luo ◽  
Teng Wang ◽  
Shengji Wei ◽  
Mingsheng Liao ◽  
Jianya Gong
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Active Tectonics ◽  
Tibet Plateau ◽  
Coseismic Deformation ◽  
Earthquake Catalog ◽  
Sar Images ◽  
Weak Surface ◽  
Phase Screens ◽  
Atmospheric Delays

Small-to-moderate earthquakes (e.g. ≤Mw5.5) occur much more frequently than large ones (e.g. >Mw6.0), yet are difficult to study with InSAR due to their weak surface deformation that are severely contaminated by atmospheric delays. Here we propose a stacking method using time-series SAR images that can effectively suppress atmospheric phase screens and extract weak coseismic deformation in centimeter to sub-centimeter level. Using this method, we successfully derive coseismic surface deformations for three small-to-moderate (Mw∼5) earthquakes in Tibet Plateau and Tienshan region from time-series Sentinel-1 SAR images, with peak line-of-sight deformation ranging from 5–6 mm to 13 mm. We also propose a strategy to downsample interferograms with weak deformation signal based on quadtree mesh obtained from preliminary slip model. With the downsampled datasets, we invert for the centroid locations, fault geometries and slips of these events. Our results demonstrate the potential of using time-series InSAR images to enrich earthquake catalog with geodetic observations for further study of earthquake cycle and active tectonics.

scholarly journals Permafrost Soil Moisture Monitoring Using Multi-Temporal TerraSAR-X Data in Beiluhe of Northern Tibet, China

2018 ◽  
Vol 10 (10) ◽  
pp. 1577 ◽  
Author(s):  
Chao Wang ◽  
Zhengjia Zhang ◽  
Simonetta Paloscia ◽  
Hong Zhang ◽  
Fan Wu ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Winter Season ◽  
Tibet Plateau ◽  
Permafrost Soil ◽  
Permafrost Region ◽  
Backscattering Coefficient ◽  
Sar Images ◽  
Northern Tibet ◽  
Variation Patterns

Global change has significant impact on permafrost region in the Tibet Plateau. Soil moisture (SM) of permafrost is one of the most important factors influencing the energy flux, ecosystem, and hydrologic process. The objectives of this paper are to retrieve the permafrost SM using time-series SAR images, without the need of auxiliary survey data, and reveal its variation patterns. After analyzing the characteristics of time-series radar backscattering coefficients of different landcover types, a two-component SM retrieval model is proposed. For the alpine meadow area, a linear retrieving model is proposed using the TerraSAR-X time-series images based on the assumption that the lowest backscattering coefficient is measured when the soil moisture is at its wilting point and the highest backscattering coefficient represents the water-saturated soil state. For the alpine desert area, the surface roughness contribution is eliminated using the dual SAR images acquired in the winter season with different incidence angles when retrieving soil moisture from the radar signal. Before the model implementation, landcover types are classified based on their backscattering features. 22 TerraSAR-X images are used to derive the soil moisture in Beiluhe, Northern Tibet with different incidence angles. The results obtained from the proposed method have been validated using in-situ soil moisture measurements, thus obtaining RMSE and Bias of 0.062 cm3/cm3 and 4.7%, respectively. The retrieved time-series SM maps of the study area point out the spatial and temporal SM variation patterns of various landcover types.

scholarly journals Surface Deformation Monitoring of a Section of Gongyu Expressway Based on SBAS-InSAR Technology

2021 ◽  
Vol 233 ◽  
pp. 01149
Author(s):  
Ying Yang ◽  
Yifang Sun ◽  
Shihong Wu ◽  
Xuegang Dong ◽  
Hanyao Huang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Tibet Plateau ◽  
Seasonal Effect ◽  
Climate Conditions ◽  
Sar Data ◽  
Sbas Insar

It is difficult to monitor the surface deformation along the expressway for the critical climate conditions in Tibet plateau. In this paper, based on sentinel-1A SAR data, the surface deformation along the Gongyu expressway was tried to evaluate using time-series SBAS-InSAR method. The results indicate that the surface deformation in most regions is within the safe acquirement of the expressway. Moreover, the surface deformation indicates a strong seasonal effect. Finally, two special spots with dangerous surface deformation are identified along the expressway.

scholarly journals Freeze-Thaw Deformation Cycles and Temporal-Spatial Distribution of Permafrost along the Qinghai-Tibet Railway Using Multitrack InSAR Processing

2021 ◽  
Vol 13 (23) ◽  
pp. 4744
Author(s):  
Jing Wang ◽  
Chao Wang ◽  
Hong Zhang ◽  
Yixian Tang ◽  
Wei Duan ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Surface Deformation ◽  
Anthropogenic Activities ◽  
Composite Index ◽  
Buffer Zone ◽  
Absolute Error ◽  
Tibet Plateau ◽  
Permafrost Region ◽  
Index Model

The Qinghai-Tibet Railway (QTR) is the railway with the highest elevation and longest distance in the world, spanning more than 1142 km from Golmud to Lhasa across the continuous permafrost region. Due to climate change and anthropogenic activities, geological disasters such as subsidence and thermal melt collapse have occurred in the QTR embankment. To conduct the large-scale permafrost monitoring and geohazard investigation along the QTR, we collected 585 Sentinel-1A images based on the composite index model using the multitrack time-series interferometry synthetic aperture radar (MTS-InSAR) method to retrieve the surface deformation over a 3.15 × 105 km2 area along the QTR. Meanwhile, a new method for permafrost distribution mapping based on InSAR time series deformation was proposed. Finally, the seasonal deformation map and a new map of permafrost distribution along the QTR from Golmud to Lhasa were obtained. The results showed that the estimated seasonal deformation range of the 10 km buffer zone along the QTR was −50–10 mm, and the LOS deformation rate ranged from −30 to 15 mm/yr. In addition, the deformation results were validated by leveling measurements, and the range of absolute error was between 0.1 and 4.62 mm. Most of the QTR was relatively stable. Some geohazard-prone sections were detected and analyzed along the QTR. The permafrost distribution results were mostly consistent with the simulated results of Zou’s method, based on the temperature at the top of permafrost (TTOP) model. This study reveals recent deformation characteristics of the QTR, and has significant scientific implications and applicational value for ensuring the safe operation of the QTR. Moreover, our method, based on InSAR results, provides new insights for permafrost classification on the Qinghai-Tibet Plateau (QTP).

Deformation monitoring and scattering characterization using PAZ co-polarimetric SAR imagery

2021 ◽  
Author(s):  
Ling Chang ◽  
Alfred Stein
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Correlation Method ◽  
Temporal Coherence ◽  
Deformation Monitoring ◽  
Data Availability ◽  
Polarimetric Sar ◽  
Sar Images ◽  
The Real ◽  
Sar Imagery

<p>The PAZ SAR satellite, launched in 2018, routinely delivers X-band SAR (synthetic aperture radar) imagery in co-polarimetric HH and VV channels on a weekly basis. It has the potential to reveal surface elevation and deformations and to categorize scattering characteristics. Yet, few relevant experiments and studies have been carried out so far [1], probably due to the limited PAZ data availability to the public. Using a relatively small stack of 10 PAZ co-polarimetric SAR images, we investigate and demonstrate the applicability of PAZ co-polarimetric SAR imagery for monitoring surface deformation. Images were acquired between September 2019 and April 2020, covering the northern part of the Netherlands. This InSAR (interferometric SAR) time series of images allowed us to classify radar scatterers in terms of scattering mechanisms.</p><p> </p><p>A key linchpin in time series analysis for surface deformation monitoring is to identify reliable constantly coherent scatterers (CCS) and to maximize their number separately in the VV and HH channels. Sufficient and reliable CCS can facilitate spatio-temporal phase unwrapping, and map surface deformation evolution. A real-valued IRF (impulse response function) correlation method is suggested for CCS selection as it generates the CCS with exact radar location and maximum exclusion of incoherent scatterers and scatterers at the sidelobes. In this way it serves as an alternative to classical methods such as the normalized amplitude dispersion (NAD). The results of our study show that 34% CCS in the VV channel and 47% in the HH channel have an ensemble temporal coherence > 0.9 using the real-valued IRF correlation method, while 5% CCS in both the VV and the HH channel have an ensemble temporal coherence > 0.9 using the NAD method. Therefore, using the real-valued IRF correlation method we obtain better-quality results of the selected CCS.  </p><p> </p><p>By using SAR images in both the VV and HH channels, co-polarimetric phase differencing (CPD) can be applied to classify the CCS into three classes: surface scattering, dihedral scattering and volume scattering. The results of our study show that by predefining an allowable noise range, in our study equal to 0.4, and using the temporal averaged CPD, we can achieve a reliable CPD-based classification. A higher percentage of CCS in the VV channel is classified as dihedral scatterers (24%), while a higher percentage of CCS in the HH channel is classified as surface scatterers (36%) and volume scatterers (47%).</p><p> </p><p>We conclude that PAZ co-polarimetric SAR imagery improves monitoring of surface deformation as compared to existing methods, and is suited to characterize radar scatterers.</p><p> </p><p>[1] Ling Chang and Alfred Stein (2020). Exploring PAZ co-polarimetric SAR data for surface movement mapping and scattering characterization. International Journal of Applied Earth Observation and Geoinformation. (https://doi.org/10.1016/j.jag.2020.102280)</p>

Evaluating ScanSAR Interferometry Deformation Time Series Using Bursted Stripmap Data

2011 ◽  
Vol 49 (6) ◽  
pp. 2335-2342 ◽  
Author(s):  
Sean M. Buckley ◽  
Krishnavikas Gudipati
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Image Pair ◽  
Sar Images ◽  
Interferometric Phase ◽  
Burst Pattern ◽  
Burst Synchronization ◽  
Small Baseline

We demonstrate scanning synthetic aperture radar (ScanSAR) advanced radar interferometry processing for surface deformation time series analysis. We apply the small baseline subsets (SBAS) technique to ScanSAR data synthesized from 40 ERS-1 and ERS-2 stripmap SAR images over known deformation in Phoenix, Arizona. The strategy is to construct a burst pattern similar to Envisat ScanSAR data for two scenarios, namely, an idealized 100% burst overlap case and a realistic variable-burst synchronization case in which any image pair has at least 50% burst overlap. We And this latter scenario to be reasonable based on an assessment of the effect of burst overlap on Phoenix interferometric phase coherence. The differences between the variable burst overlap ScanSAR and stripmap SAR SBAS-derived pixel velocities have a mean of 0.02 cm/year and a standard deviation of 0.02 cm/year. It is noted that one can expect SBAS velocity and displacement one-sigma errors of 0.1 cm/year and 0.5 cm, respectively, from multilooked stripmap data. We observe that 96% and 99% of the variable burst overlap ScanSAR pixel velocities are within ±0.1 and ±0.2 cm/year (one- and two-sigma), respectively, of our stripmap SAR pixel velocities. These results are similar to those reported for SBAS analysis applied to low-resolution multilook interferograms derived from coherence-preserving down sampling of stripmap data. We also And that the rms deviations between variable burst overlap ScanSAR and stripmap SBAS displacement estimates are 0.40 ± 0.30 cm. 68% and 94% of the variable burst overlap ScanSAR pixel displacements are within ±0.5 and ±1.0 cm, respectively, of the stripmap displacements.

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 Time-series snowmelt detection over the Antarctic using Sentinel-1 SAR images on Google Earth Engine

2021 ◽  
Vol 256 ◽  
pp. 112318
Author(s):  
Dong Liang ◽  
Huadong Guo ◽  
Lu Zhang ◽  
Yun Cheng ◽  
Qi Zhu ◽  
...  
Keyword(s):  
Time Series ◽  
Google Earth ◽  
Sar Images ◽  
Google Earth Engine ◽  
The Antarctic

scholarly journals GPS measurements on pre-, co- and post-seismic surface deformation at first multi-parametric geophysical observatory, Ghuttu in Garhwal Himalaya, India

2020 ◽  
Vol 10 (1) ◽  
pp. 136-144
Author(s):  
P.K. Gautam ◽  
S. Rajesh ◽  
N. Kumar ◽  
C.P. Dabral
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Translational Motion ◽  
Anomalous Behavior ◽  
Deformation Pattern ◽  
Local Earthquakes ◽  
Position Time Series ◽  
Continuous Gps ◽  
Gps Time Series ◽  
Gps Station

Abstract We investigate the surface deformation pattern of GPS station at MPGO Ghuttu (GHUT) to find out the cause of anomalous behavior in the continuous GPS time series. Seven years (2007-2013) of GPS data has been analyzed using GAMIT/GLOBK software and generated the daily position time series. The horizontal translational motion at GHUT is 43.7 ± 1 mm/yr at an angle of 41°± 3° towards NE, while for the IGS station at LHAZ, the motion is 49.4 ±1 mm/yr at 18 ± 2.5° towards NEE. The estimated velocity at GHUT station with respect to IISC is 12 ± 1 mm/yr towards SW. Besides, we have also examined anomalous changes in the time series of GHUT before, after and during the occurrences of local earthquakes by considering the empirical strain radius; such that, a possible relationship between the strain radius and the occurrences of earthquakes have been explored. We considered seven local earthquakes on the basis of Dobrovolsky strain radius condition having magnitude from 4.5 to 5.7, which occurred from 2007 to 2011. Results show irrespective of the station strain radius, pre-seismic surface deformational anomalies are observed roughly 70 to 80 days before the occurrence of a Moderate or higher magnitude events. This has been observed for the cases of those events originated from the Uttarakashi and the Chamoli seismic zones in the Garhwal and Kumaun Himalaya. Occurrences of short (< 100 days) and long (two years) inter-seismic events in the Garhwal region plausibly regulating and diffusing the regional strain accumulation.

scholarly journals Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

2019 ◽  
Vol 93 (12) ◽  
pp. 2651-2660 ◽  
Author(s):  
Sergey Samsonov
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Three Dimensional ◽  
Data Sets ◽  
Ice Flow ◽  
The North ◽  
Glacier Ice ◽  
Deformation Component ◽  
3D Deformation

AbstractThe previously presented Multidimensional Small Baseline Subset (MSBAS-2D) technique computes two-dimensional (2D), east and vertical, ground deformation time series from two or more ascending and descending Differential Interferometric Synthetic Aperture Radar (DInSAR) data sets by assuming that the contribution of the north deformation component is negligible. DInSAR data sets can be acquired with different temporal and spatial resolutions, viewing geometries and wavelengths. The MSBAS-2D technique has previously been used for mapping deformation due to mining, urban development, carbon sequestration, permafrost aggradation and pingo growth, and volcanic activities. In the case of glacier ice flow, the north deformation component is often too large to be negligible. Historically, the surface-parallel flow (SPF) constraint was used to compute the static three-dimensional (3D) velocity field at various glaciers. A novel MSBAS-3D technique has been developed for computing 3D deformation time series where the SPF constraint is utilized. This technique is used for mapping 3D deformation at the Barnes Ice Cap, Baffin Island, Nunavut, Canada, during January–March 2015, and the MSBAS-2D and MSBAS-3D solutions are compared. The MSBAS-3D technique can be used for studying glacier ice flow at other glaciers and other surface deformation processes with large north deformation component, such as landslides. The software implementation of MSBAS-3D technique can be downloaded from http://insar.ca/.

Sign in / Sign up

Export Citation Format

Share Document