High surface displacement monitoring with persistent scatterer interferometry

2012 ◽  
Author(s):  
Zahra Sadeghi ◽  
Mohammad Javad Valadan Zouj ◽  
Maryam Dehghani
Keyword(s):  
High Surface ◽  
Surface Displacement ◽  
Displacement Monitoring ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterer

scholarly journals Monitoring the Vulnerability of the Dam and Dikes in Germano Iron Mining Area after the Collapse of the Tailings Dam of Fundão (Mariana-MG, Brazil) Using DInSAR Techniques with TerraSAR-X Data

2018 ◽  
Vol 10 (10) ◽  
pp. 1507 ◽  
Author(s):  
José Mura ◽  
Fábio Gama ◽  
Waldir Paradella ◽  
Priscila Negrão ◽  
Samuel Carneiro ◽  
...  
Keyword(s):  
Surface Displacement ◽  
Mining Area ◽  
Mining Waste ◽  
Tailings Dam ◽  
Persistent Scatterer Interferometry ◽  
Spatiotemporal Information ◽  
Heavy Equipment ◽  
Persistent Scatterer ◽  
Iron Mining ◽  
Small Baseline

The Fundão tailings dam in the Germano iron mining complex (Mariana, Brazil) collapsed on the afternoon of 5 November 2015, and around 32.6 million cubic meters of mining waste spilled from the dam, causing polluion with mining waste along a trajectory of 668 km, extending to the Atlantic Ocean. The Sela & Tulipa and Selinha dikes, and the main Germano tailings dam, were directly or indirectly affected by the accident. This work presents an investigation using Advanced-Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques for risk assessment in these critical structures during 18 months after the catastrophic event. The approach was based on the integration of SBAS (Small Baseline Subset) and PSI (Persistent Scatterer Interferometry) techniques, aiming at detecting linear and nonlinear ground displacements in these mining structures. It used a set of 48 TerraSAR-X images acquired on ascending mode from 11 November 2015 to 15 May 2017. The results provided by the A-DInSAR analysis indicated an overall stability in the dikes and in the main wall of Germano tailings dam, which is in agreement with in situ topographic monitoring. In addition, it was possible to detect areas within the reservoir showing accumulated values of up to −125 mm of subsidence, probably caused by settlements of the waste dry material due to the interruption of the mining waste deposition, and values up to −80 mm on auxiliary dikes, probably caused by continuous traffic of heavy equipment. The spatiotemporal information of surface displacement of this large mining structure can be used for future operational planning and risk control.

scholarly journals Applying persistent scatterer interferometry for surface displacement mapping in the Azul open pit manganese mine (Amazon region) with TerraSAR-X StripMap data

2015 ◽  
Vol 9 (1) ◽  
pp. 095978 ◽  
Author(s):  
Carolina de Athayde Pinto ◽  
Waldir Renato Paradella ◽  
José Claudio Mura ◽  
Fabio Furlan Gama ◽  
Athos Ribeiro dos Santos ◽  
...  
Keyword(s):  
Surface Displacement ◽  
Amazon Region ◽  
Open Pit ◽  
Persistent Scatterer Interferometry ◽  
Displacement Mapping ◽  
Persistent Scatterer

scholarly journals Implementation of Non-Linear Non-Parametric Persistent Scatterer Interferometry and Its Robustness for Displacement Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1004
Author(s):  
Fumitaka Ogushi ◽  
Masashi Matsuoka ◽  
Marco Defilippi ◽  
Paolo Pasquali
Keyword(s):  
Data Processing ◽  
Surface Displacement ◽  
Real Data ◽  
Velocity Spectrum ◽  
Persistent Scatterer Interferometry ◽  
Implementation Phase ◽  
The Real ◽  
Persistent Scatterer ◽  
Non Linear ◽  
Non Parametric

To derive surface displacement, interferometric stacking with synthetic aperture radar (SAR) data is commonly used, and this technique is now in the implementation phase in the real world. Persistent scatterer interferometry (PSI) is one of the most universal approaches among in- terferometric stacking techniques, and non-linear non-parametric PSI (NN-PSI) was proposed to overcome the drawbacks of PSI approaches. The estimation of the non-linear displacements was successfully conducted using NN-PSI. However, the estimation of NN-PSI is not always stable with certain displacements because wider range of the velocity spectrum is used in NN-PSI than the conventional approaches; therefore, a calculation procedure and parameter optimization are needed to consider. In this paper, optimized parameters and procedures of NN-PSI are proposed, and real data processing with Sentinel-1 in the Kanto region in Japan was conducted. We confirmed that the displacement estimation was comparable to the measurement of the permanent global positioning system (GPS) stations, and the root mean square error between the GPS measurement and NN-PSI estimation was less than 3 mm in two years. The displacement over 2π ambiguity, which the conventional PSI approach wrongly reconstructed, was also quantitatively validated and successfully estimated by NN-PSI. As a result of the real data processing, periodical displacements were also reconstructed through NN-PSI. We concluded that the NN-PSI approach with the proposed parameters and method enabled the estimation of several types of surface displacements that conventional PSI approaches could not reconstruct.

scholarly journals Displacement Monitoring and Health Evaluation of Two Bridges Using Sentinel-1 SAR Images

2018 ◽  
Vol 10 (11) ◽  
pp. 1714 ◽  
Author(s):  
Qihuan Huang ◽  
Oriol Monserrat ◽  
Michele Crosetto ◽  
Bruno Crippa ◽  
Yian Wang ◽  
...  
Keyword(s):  
High Speed ◽  
Health State ◽  
Displacement Monitoring ◽  
Persistent Scatterer Interferometry ◽  
Sar Images ◽  
Persistent Scatterer ◽  
The Difference ◽  
Metal Properties ◽  
Thermal Dilation ◽  
Bridge Length

Displacement monitoring of large bridges is an important source of information concerning their health state. In this paper, a procedure based on satellite Persistent Scatterer Interferometry (PSI) data is presented to assess bridge health. The proposed approach periodically assesses the displacements of a bridge in order to detect abnormal displacements at any position of the bridge. To demonstrate its performances, the displacement characteristics of two bridges, the Nanjing-Dashengguan High-speed Railway Bridge (NDHRB, 1272 m long) and the Nanjing-Yangtze River Bridge (NYRB, 1576-m long), are studied. For this purpose, two independent Sentinel-1 SAR datasets were used, covering a two-year period with 75 and 66 images, respectively, providing very similar results. During the observed period, the two bridges underwent no actual displacements: thermal dilation displacements were dominant. For NDHRB, the total thermal dilation parameter from the PSI analysis was computed using the two different datasets; the difference of the two computations was 0.09 mm/°C, which, assuming a temperature variation of 30 °C, corresponds to a discrepancy of 2.7 mm over the total bridge length. From the total thermal dilation parameters, the coefficients of thermal expansion (CTE) were calculated, which were 11.26 × 10−6/°C and 11.19 × 10−6/°C, respectively. These values match the bridge metal properties. For NYRB, the estimated CTE was 10.46 × 10−6/°C, which also matches the bridge metal properties (11.26 × 10−6/°C). Based on a statistical analysis of the PSI topographic errors of NDHRB, pixels on the bridge deck were selected, and displacement models covering the entire NDHRB were established using the two track datasets; the model was validated on the six piers with an absolute mean error of 0.25 mm/°C. Finally, the health state of NDHRB was evaluated with four more images using the estimated models, and no abnormal displacements were found.

scholarly journals Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

2019 ◽  
Vol 11 (14) ◽  
pp. 1675 ◽  
Author(s):  
Tomás ◽  
Pagán ◽  
Navarro ◽  
Cano ◽  
Pastor ◽  
...  
Keyword(s):  
Regional Scale ◽  
Central Italy ◽  
Geographical Information ◽  
External Information ◽  
Automatic Identification ◽  
Persistent Scatterer Interferometry ◽  
Active Deformation ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Map Scale

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

Sign in / Sign up

Export Citation Format

Share Document