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 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 InSAR Analysis of the Small Baseline Subset to Estimate Surface Deformation at Mt. Bromo Indonesia

Teknik ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 126
Author(s):  
Arliandy Pratama Arbad ◽  
Wataru Takeuchi ◽  
Yosuke Aoki ◽  
Achmad Ardy ◽  
Mutiara Jamilah
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Sar Interferometry ◽  
Alos Palsar ◽  
Small Baseline Subset ◽  
Sar Data ◽  
Small Baseline

Penginderaan jauh kini memainkan peranan penting dalam pengamatan perilaku gunung api. Penelitian ini bertujuan untuk mengamati deformasi permukaan Gunung Bromo, yang terletak di Jawa bagian Timur, Indonesia, yang masuk dalam rangkaian sistem volkanik di Taman Nasional Bukit Tengger Semeru (TNBTS). Penggunaan algoritma SAR Interferometry (InSAR) yang disebut sebagai pendekatan Small Baseline Subset (SBAS) memungkinkan perancangan peta kecepatan deformasi rata-rata dan and peta time series displacement di wilayah kajian. Teknik SBAS yang biasa menghasilkan rangkaian observasi tahap interferometrik. Ini tercatat sebagai kombinasi linear dari nilai fase SAR  scene untuk setiap pixel secara tersendiri. Analisis yang dilakukan terutama berdasarkan 22 data SAR data yang diperoleh melalui sensor ALOS/PALSAR selama kurun waktu 2007–2011. Beberapa penelitian menunjukkan bahwa kemampuan analisis InSAR dalam menyelidiki siklus gunung api, terutama Gunung Bromo yang memiliki karakteristik erupsi stratovolcano dalam satu hingga lima tahun. Analisis hasil memperlihatkan adanya kemajuan dari kajian sebelumnya akan InSAR wilayah tersebut, yang lebih fokus  kepada deformasi yang berpengaruh kepada kaldera. Hal ini menunjukkan bahwa penelitian ini bisa diimplementasikan pada manajemen risiko atau manajemen infrastruktur

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 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.

An extended GeoNode-Based Platform for Detailed Analysis of the Spatial/Temporal DInSAR Information Contents

2020 ◽  
Author(s):  
Adele Fusco ◽  
Sabatino Buonanno ◽  
Giovanni Zeni ◽  
Michele Manunta ◽  
Maria Marsella ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Spatial Data ◽  
High Performance ◽  
Surface Deformation ◽  
Surface Displacement ◽  
Synthetic Aperture ◽  
Sar Data ◽  
Informative Content ◽  
Aperture Radar

<p>We present an efficient tool for managing, visualizing, analysing, and integrating with other data sources, Earth Observation (EO) data for the analysis of surface deformation phenomena. In particular, we focused on specific <span>E</span><span>O</span> data that are those obtained by an <span>a</span><span>dvanced</span>-processing of Synthetic Aperture Radar (SAR) data for monitoring wide areas of the Earth's surface. More specifically, <span>we refer to the </span><span>SAR technique called </span><span>advanced differential interferometric synthetic aperture radar </span><span>(</span><span>DInSAR</span><span>)</span> <span>that </span><span>have demonstrated </span><span>its</span><span> capabilit</span><span>ies</span><span> to detect, </span><span>to </span><span>map and </span><span>to </span><span>analyse the on-going surface displacement phenomena, </span><span>both spatially and temporally, </span><span>with centimetre to millimetre accuracy t</span><span>hanks to the</span><span> generat</span><span>ion of</span><span> deformation maps and time-series</span>. Currently, the DInSAR scenario is characterized by a huge availability of SAR data acquired during the last 25 years, now with a massive and ever-increasing data flow supplied by the C-band Sentinel-1 (S1) constellation of the European Copernicus program.</p><p align="justify"><span>Considering this big picture, the Spatial Data Infrastructures (SDI) becomes a fundamental tool to implement a framework to handle the informative content of geographic data. Indeed, an SDI represents a collection of technologies, policies, standards, human resources, and related activities permitting the acquisition, processing, distribution, use, maintenance, and preservation of spatial data. </span></p><p align="justify"><span>We implemented an SDI, extending the functionalities of GeoNode, which is a web-based platform, providing an open-source framework based on the Open Geospatial Consortium (OGC) standards. </span><span>OGC</span> <span>makes easier</span><span> interoperability functionalities, </span><span>that represent an extremely important </span><span>aspect because allow the data producers to share geospatial information for all types of cooperative processes, avoiding duplication of efforts and costs. Our </span><span>implemented</span><span> GeoNode-Based Platform </span><span>extends a Geographic Information System (GIS) to a web-accessible resource and </span><span>adapt</span><span>s the SDI tools </span><span>to DInSAR-related requirements. </span></p><p align="justify"><span>O</span><span>ur efforts have been dedicated to enabling the GeoNode platform to effectively analyze and visualize the spatial/temporal characteristics of the DInSAR deformation time-series and their related products. Moreover, the implemented multi-thread based new functionalities allow us to efficiently upload and update large data volumes of the available DInSAR results into a dedicated geodatabase. </span><span>W</span><span>e </span><span>demonstrate the high performance of implemented</span><span> GeoNode-Based Platform, </span><span>showing </span><span>DInSAR results relevant to the acquisitions of the Sentinel-1 constellation, collected during 2015-2018 </span><span>over Italy</span><span>.</span></p><p align="justify">This work is supported by the 2019-2021 IREA CNR and Italian Civil Protection Department agreement; the H2020 EPOS-SP project (GA 871121); the I-AMICA (PONa3_00363) project; and the IREA-CNR/DGSUNMIG agreement.</p><p> </p><p> </p>

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 Detecting and Analyzing the Evolution of Subsidence Due to Coal Fires in Jharia Coalfield, India Using Sentinel-1 SAR Data

2021 ◽  
Vol 13 (8) ◽  
pp. 1521
Author(s):  
Moidu Jameela Riyas ◽  
Tajdarul Hassan Syed ◽  
Hrishikesh Kumar ◽  
Claudia Kuenzer
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Surface Deformation ◽  
Early Warning Systems ◽  
Temporal Variations ◽  
Landsat 8 ◽  
Jharia Coalfield ◽  
Field Evidence ◽  
Coal Fires ◽  
Sar Data

Public safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequently decomposed to derive precise vertical subsidence estimates. The most prominent subsidence (~22 cm) is observed in Kusunda colliery. The subsidence regions also correspond well with the Landsat-8 based thermal anomaly map and field evidence. Subsequently, the vertical surface deformation time-series is analyzed to characterize temporal variations within the 9.5 km2 area of coal fires. Results reveal that nearly 10% of the coal fire area is newly formed, while 73% persisted throughout the study period. Vulnerability analyses performed in terms of the susceptibility of the population to land surface collapse demonstrate that Tisra, Chhatatanr, and Sijua are the most vulnerable towns. Our results provide critical information for developing early warning systems and remediation strategies.

scholarly journals SURFACE DEFORMATION MONITORING IN PERMAFROST REGIONS OF TIBETAN PLATEAU BASED ON ALOS PALSAR DATA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1509-1512
Author(s):  
L. M. Chen ◽  
G. Qiao ◽  
P. Lu
Keyword(s):  
Structural Damage ◽  
Large Scale ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Frozen Soil ◽  
Tibet Plateau ◽  
Temperature Deformation ◽  
Deformation Pattern ◽  
Permafrost Region ◽  
Freeze Thaw

The permafrost region of Qinghai-Tibet Plateau is widely distributed with the freeze/thaw processes that cause surface structural damage. The differential interferometry synthetic aperture radar (DInSAR) can detect large scale surface deformation with high precision, thus can be used to monitor the freeze/thaw processes of frozen soil area. In this paper, the surface deformation pattern of Qinghai-Tibet railway was analyzed by using the PALSAR 1.0 raw data of the ALOS satellite (L band) and 90m resolution SRTM DEM data, with the help of two-pass DInSAR method in GAMMA software, and the differential interferograms and deformation maps were obtained accordingly. Besides, the influence of temperature, topography and other factors on deformation of frozen soil were also studied. The following conclusions were obtained: there is a negative correlation between deformation and temperature, and there is a delay between the deformation change and that of temperature; deformation and elevation are positively correlated; the permafrost deformation is also affected by solar radiation that could form variable amplitude variation.

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