scholarly journals Satellite interferometry for mapping surface deformation time series in one, two and three dimensions: A new method illustrated on a slow-moving landslide

2020 ◽  
Vol 266 ◽  
pp. 105471 ◽  
Author(s):  
Sergey Samsonov ◽  
Antoine Dille ◽  
Olivier Dewitte ◽  
François Kervyn ◽  
Nicolas d'Oreye
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Three Dimensions ◽  
New Method ◽  
Slow Moving

A new methodology to detect changes in displacement rates of slow-moving landslides using InSAR time series

2021 ◽  
Author(s):  
Alexandra Urgilez Vinueza ◽  
Alexander Handwerger ◽  
Mark Bakker ◽  
Thom Bogaard
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Piecewise Linear ◽  
Regional Scale ◽  
Ground Surface ◽  
Surface Displacement ◽  
Information Criterion ◽  
Piecewise Linear Function ◽  
Linear Segment ◽  
Slow Moving

<p>Regional-scale landslide deformation can be measured using satellite-based synthetic aperture radar interferometry (InSAR). Our study focuses on the quantification of displacements of slow-moving landslides that impact a hydropower dam and reservoir in the tropical Ecuadorian Andes. We constructed ground surface deformation time series using data from the Copernicus Sentinel-1 A/B satellites between 2016 and 2020. We developed a new approach to automatically detect the onset of accelerations and/or decelerations within each active landslide. Our approach approximates the movement of a pixel as a piecewise linear function. Multiple linear segments are fitted to the cumulative deformation time series of each pixel. Each linear segment represents a constant movement. The point where one linear segment is connected to another linear segment represents the time when the pixel’s rate of movement has changed from one value to another value and is referred to as a breakpoint. As such, the breakpoints represent moments of acceleration or deceleration. Three criteria are used to determine the number of breakpoints: the timing and uncertainty of the breakpoints, the confidence intervals of the fitted segments’ slopes, and the Akaike Information Criterion (AIC). The suitable number of breakpoints for each pixel (i.e., the number of accelerations or decelerations) is determined by finding the largest number of breakpoints that complies with the three listed criteria. The application of this approach to landslides results in a wealth of information on the surface displacement of a slope and an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of acceleration and deceleration can further be used to study the physical behavior of a slow-moving slope or for (regional) hazard assessment linking the onset of change in displacement rate to causal and triggering factors.</p>

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 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/.

scholarly journals A New Method for Fusion of Measured and Model-derived Solar Radiation Time-series

2014 ◽  
Vol 48 ◽  
pp. 1617-1626 ◽  
Author(s):  
Theresa Mieslinger ◽  
Felix Ament ◽  
Kaushal Chhatbar ◽  
Richard Meyer
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
New Method ◽  
Radiation Time

scholarly journals SUBSIDENCE EVALUATION OF HIGH-SPEED RAILWAY IN SHENYANG BASED ON TIME-SERIES INSAR

2018 ◽  
Vol IV-3 ◽  
pp. 273-276
Author(s):  
Yun Zhang ◽  
Lianhuan Wei ◽  
Jiayu Li ◽  
Shanjun Liu ◽  
Yachun Mao ◽  
...  
Keyword(s):  
Time Series ◽  
High Speed ◽  
Cross Validation ◽  
Surface Deformation ◽  
Local Environment ◽  
Local Area ◽  
Safe Operation ◽  
High Speed Rail ◽  
High Speed Railway ◽  
Under Construction

More and more high-speed railway are under construction in China. The slow settlement along high-speed railway tracks and newly-built stations would lead to inhomogeneous deformation of local area, and the accumulation may be a threat to the safe operation of high-speed rail system. In this paper, surface deformation of the newly-built high-speed railway station as well as the railway lines in Shenyang region will be retrieved by time series InSAR analysis using multi-orbit COSMO-SkyMed images. This paper focuses on the non-uniform subsidence caused by the changing of local environment along the railway. The accuracy of the settlement results can be verified by cross validation of the results obtained from two different orbits during the same period.

scholarly journals A New Method to Detect Outliers in High-frequency Time Series

2018 ◽  
Vol 8 (1) ◽  
pp. 16
Author(s):  
Ilaria Lucrezia Amerise ◽  
Agostino Tarsitano
Keyword(s):  
Time Series ◽  
High Frequency ◽  
Time Series Data ◽  
New Method ◽  
Series Data ◽  
Absolute Difference ◽  
Data Preparation ◽  
Simple Method ◽  
Pass Through ◽  
Nonparametric Procedure

The objective of this research is to develop a fast, simple method for detecting and replacing extreme spikes in high-frequency time series data. The method primarily consists&nbsp; of a nonparametric procedure that pursues a balance between fidelity to observed data and smoothness. Furthermore, through examination of the absolute difference between original and smoothed values, the technique is also able to detect and, where necessary, replace outliers with less extreme data. Unlike other filtering procedures found in the literature, our method does not require a model to be specified for the data. Additionally, the filter makes only a single pass through the time series. Experiments&nbsp; show that the new method can be validly used as a data preparation tool to ensure that time series modeling is supported by clean data, particularly in a complex context such as one with high-frequency data.

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