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>

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.

Monitoring Three Gorge Area Landslide currently movement by Mutilplatform SAR Interferometry

2020 ◽  
Author(s):  
Tao Li ◽  
Yangmao Wen ◽  
Lulu Chen ◽  
Jinge Wang
Keyword(s):  
High Resolution ◽  
Surface Deformation ◽  
Test Site ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Sar Image ◽  
Landslide Area ◽  
Sar Images ◽  
The Past ◽  
Huangtupo Landslide

<p>Three Gorge area landslide hazards developed very fast after the Dam started to impound the water since 2007. There were lots of research literatures concentrated on the Badong Huangtupo Landslide area for the whole city center had to change its position in 2009. Several literatures used Envisat SAR images time series to monitoring the surface deformation from 2008~2010. The results showed good consistent with the water level changes and precipitation.  The high resolution TerraSAR Spotlight images had been used to monitoring the Shuping landslide and Fanjiaping landslide area in Zigui country from 2009~2012,the InSAR results showed good details of the landslide boundary and deformation rate with DInSAR technology.</p><p>This paper studies several landslide area in the Three Gorge by InSAR technology in the past few years, such as Huangtupo, Huanglashi , Daping and  Baiheping landslide area , etc. al . The high resolution SAR images covered Badong and Wushan area have been collected, including the Sentinel-1, TerraSAR, RadarSAT-2, ALOS-2 SAR images. The high resolution topography in those landslide area have been collected both by UAV lidar and high resolution topography map.</p><p>The Huangtupo landslide area changed a lot in the past 3 years with the buildings ruins cleared and red soil covered by the local government. The time series results by Sentinel data in this area shows the big changes but could not derive reasonable deformation results.</p><p>Three Gorges Research Center for Geo-hazards (TGRC) of China University of Geosciences(CUG) built the Badong field test site in Huangtupo landslide area. This test site is composed with a tunnel group and a series of monitoring system including the inside sensors, surface deformation monitoring sensors and so on. In this paper, we mounted several new designed dihedral corner reflectors on the Huangtupo landslide area for high precision deformation monitoring by InSAR. Both the  ascending and the  descending orbit data of RadarSAT-2 high resolution SAR image  and TerraSAR Spotlight images have been collected in this field.</p><p>The preliminary results from those new acquiring SAR data series show that the traditional landslide area such as Huanglashi , Daping, Baiheping are all moving slowly with good coherence in SAR image series.  The poor vegetation coverage in those landslide area helped to get the credible  InSAR results. The high resolution DEM is the critical elements for the DInSAR techniques in those landslide area. The steep  topography in those landslide area distorted the SAR images correspondingly.</p><p>Our results shows that it is possible to use ascending and descending high resolution SAR images to monitor the landslide area with mm level precision, while the vegetation is not so dense. High resolution SAR interferometry helped a lot for the landslide boundary detection and detailed analysis. The lower resolution SAR images such as Sentinel-1 still could provide some deformation results in landslide area, but it need more auxiliary data to interpret the results.</p>

scholarly journals Similarity measures of full polarimetric SAR images fusion for improved SAR image matching

2015 ◽  
Vol XL-7/W4 ◽  
pp. 13-16 ◽  
Author(s):  
H. Ding
Keyword(s):  
Similarity Measure ◽  
Image Matching ◽  
Stereo Matching ◽  
Similarity Measures ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Sar Data ◽  
Sar Imagery ◽  
Airborne Sar

China’s first airborne SAR mapping system (CASMSAR) developed by Chinese Academy of Surveying and Mapping can acquire high-resolution and full polarimetric (HH, HV, VH and VV) Synthetic aperture radar (SAR) data. It has the ability to acquire X-band full polarimetric SAR data at a resolution of 0.5m. However, the existence of speckles which is inherent in SAR imagery affects visual interpretation and image processing badly, and challenges the assumption that conjugate points appear similar to each other in matching processing. In addition, researches show that speckles are multiplicative speckles, and most similarity measures of SAR image matching are sensitive to them. Thus, matching outcomes of SAR images acquired by most similarity measures are not reliable and with bad accuracy. Meanwhile, every polarimetric SAR image has different backscattering information of objects from each other and four polarimetric SAR data contain most basic and a large amount of redundancy information to improve matching. Therefore, we introduced logarithmically transformation and a stereo matching similarity measure into airborne full polarimetric SAR imagery. Firstly, in order to transform the multiplicative speckles into additivity ones and weaken speckles' influence on similarity measure, logarithmically transformation have to be taken to all images. Secondly, to prevent performance degradation of similarity measure caused by speckles, measure must be free or insensitive of additivity speckles. Thus, we introduced a stereo matching similarity measure, called Normalized Cross-Correlation (NCC), into full polarimetric SAR image matching. Thirdly, to take advantage of multi-polarimetric data and preserve the best similarity measure value, four measure values calculated between left and right single polarimetric SAR images are fused as final measure value for matching. The method was tested for matching under CASMSAR data. The results showed that the method delivered an effective performance on experimental imagery and can be used for airborne SAR matching applications.

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 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 Change Detection in Time Series of Polarimetric SAR Images

2021 ◽  
pp. 35-71
Author(s):  
Knut Conradsen ◽  
Henning Skriver ◽  
Morton J. Canty ◽  
Allan A. Nielsen
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Polarimetric Sar ◽  
Sar Images

scholarly journals Statistical Analysis of Changes in Sentinel-1 Time Series on the Google Earth Engine

2019 ◽  
Vol 12 (1) ◽  
pp. 46 ◽  
Author(s):  
Morton J. Canty ◽  
Allan A. Nielsen ◽  
Knut Conradsen ◽  
Henning Skriver
Keyword(s):  
Time Series ◽  
Google Earth ◽  
Data Availability ◽  
Anthropogenic Activity ◽  
Time Data ◽  
Software Interface ◽  
Recent Modification ◽  
Disaster Assessment ◽  
Google Earth Engine ◽  
Sar Imagery

Time series analysis of Sentinel-1 SAR imagery made available by the Google Earth Engine (GEE) is described. Advantage is taken of a recent modification of a sequential complex Wishart-based algorithm which is applicable to the dual polarization intensity data archived on the GEE. Both the algorithm and a software interface to the GEE Python API for convenient data exploration and analysis are presented; the latter can be run from a platform independent Docker container and the source code is available on GitHub. Application examples are given involving the monitoring of anthropogenic activity (shipping, uranium mining, deforestation) and disaster assessment (flash floods). These highlight the advantages of the good temporal resolution resulting from cloud cover independence, short revisit times and near real time data availability.

scholarly journals Surface Deformation Monitoring in Zhengzhou City from 2014 to 2016 Using Time-Series InSAR

2018 ◽  
Vol 10 (11) ◽  
pp. 1731 ◽  
Author(s):  
Zhengjia Zhang ◽  
Chao Wang ◽  
Mengmeng Wang ◽  
Ziwei Wang ◽  
Hong Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Urban Expansion ◽  
Correction Method ◽  
Deformation Monitoring ◽  
Ground Subsidence ◽  
Significant Information ◽  
Persistent Scatterers ◽  
Deformation Parameters

In recent years, with the development of urban expansion in Zhengzhou city, the underground resources, such as underground water and coal mining, have been exploited greatly, which have resulted in ground subsidence and several environmental issues. In order to study the spatial distribution and temporal changes of ground subsidence of Zhengzhou city, the Interferometric Synthetic Aperture Radar (InSAR) time series analysis technique combining persistent scatterers (PSs) and distributed scatterers (DSs) was proposed and applied. In particular, the orbit and topographic related atmospheric phase errors have been corrected by a phase ramp correction method. Furthermore, the deformation parameters of PSs and DSs are retrieved based on a layered strategy. The deformation and DEM error of PSs are first estimated using conventional PSI method. Then the deformation parameters of DSs are retrieved using an adaptive searching window based on the initial results of PSs. Experimental results show that ground deformation of the study area could be retrieved by the proposed method and the ground deformation is widespread and unevenly distributed with large differences. The deformation rate ranges from −55 to 10 mm/year, and the standard deviation of the results is about 8 mm/year. The observed InSAR results reveal that most of the subsidence areas are in the north and northeast of Zhengzhou city. Furthermore, it is found that the possible factors resulting in the ground subsidence include sediment consolidation, water exploitation, and urban expansion. The result could provide significant information to serve the land subsidence mitigation in Zhengzhou city.

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