ExistingTrack Deformation Models

2011 ◽  
pp. 163-180
Keyword(s):  
Deformation Models

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.

Junction deformation models for asperities in sliding interaction

Wear ◽  
1972 ◽  
Vol 20 (1) ◽  
pp. 73-87 ◽  
Author(s):  
P.K. Gupta ◽  
N.H. Cook
Keyword(s):  
Deformation Models

3-D Heterogeneous Elastic Crustal Structure for Deformation Models in the Hengill Area, SW Iceland

2021 ◽  
Author(s):  
Cécile Ducrocq ◽  
Halldór Geirsson ◽  
Alex Hobé ◽  
Gylfi Páll Hersir ◽  
Thóra Árnadóttir ◽  
...  
Keyword(s):  
Crustal Structure ◽  
Power Plants ◽  
Electrical Power ◽  
Element Model ◽  
Volcanic Complex ◽  
Elastic Model ◽  
Spatial Effects ◽  
Volcanic System ◽  
Shear Moduli ◽  
Deformation Models

<p>Crustal deformation in volcanic areas relates ground motions, measured by geodetic techniques, to physical (e.g. pressure or volumetric) changes of magmatic sources below the surface. These measurements contribute to studies of<!-- this is not optimal, changing it might require rewriting the entire sentence. Perhaps you want to break this sentence into two. --> ongoing processes at the source of possible unrest, and are thus key for hazard assessment in active volcanic areas around the globe. However, such assessments often rely on geodetic-based models with quite simplistic assumptions of the physical structure of the volcanic complex. Particularly, constant values of elastic parameters (e.g. Poisson’s ratio and shear moduli) are commonly used for entire active volcanic areas, thus overlooking the spatial effects of lithological properties, depth-dependant compression and temperature variations on those parameters. These simplifications may lead to inaccurate interpretation of the location, shape, and volume change of deformation sources.</p><p> </p><p>In this study we ask how the 3-D heterogeneities of the elastic crustal structure beneath the Hengill volcanic system, SW Iceland, affects models of deformation sources in the area. The Hengill area hosts two active volcanic systems (Hengill and Hrómundartindur), and two high-enthalpy geothermal power plants (Nesjavellir and Hellisheiði), which provide thermal and electrical power to Reykjavík, the capital of Iceland, only 30 km away. To retrieve information on the spatial heterogeneities in the shear moduli and Poisson’s ratio beneath the Hengill area, we first estimate the 3-D shallow density structure of the area using results from regional and local gravimetric surveys. We implement this structure, along with seismic tomographic studies of the SW Iceland, in a Finite Element Model to solve, using forward models, for the 3-D heterogeneities in the shear moduli and Poisson’s ratio beneath the Hengill area.<!-- This might be more effective if the order of these statements is changed, for example: To achieve [stated goal] we produce [FEM] using [results from geophysics]. --> Furthermore, we discuss the difference between static and kinematic elastic moduli, which is important when building deformation models from seismic tomography.<!-- My first reaction to this statement is: "How do you address this?" This could be answered directly, except if you think it detracts from the story. --> The new 3-D inferred elastic model is then used to re-estimate parameters for different sources of deformation causing uplift and subsidence in the area in the past decades. This study shows the importance of accounting for heterogeneities in the crustal elastic structure to estimate with higher accuracy the sources of deformation in volcanic areas around the world.</p>

Tomographic reconstruction using free-form deformation models

1999 ◽  
Author(s):  
Xavier L. Battle ◽  
Yves J. Bizais ◽  
Catherine Le Rest ◽  
A. Turzo
Keyword(s):  
Tomographic Reconstruction ◽  
Free Form ◽  
Free Form Deformation ◽  
Deformation Models
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