Three-dimensional strain tensor estimation by GPS observations: methodological aspects and geophysical applications

Pietrantonio, Grazia; Riguzzi, Federica

doi:10.1016/j.jog.2004.02.021

Cited by 48 publications

(12 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To solve this problem, the above fundamental mathematical model needs to be refined. In this research, based on Equations (4) and (6), when the elevation is 90 degrees and the measurement environment is ideal, the observation precision can be regarded as the only result of receiver noise to a great extent [27,43]. It leads to the basic relations:…”

Section: Of 18mentioning

confidence: 99%

Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

Shen

Gao

et al. 2018

Remote Sensing

View full text Add to dashboard Cite

Abstract:In Global Navigation Satellite System (GNSS) positioning, observation precisions are frequently impacted by the site-specific unmodeled errors, especially for the code observations that are widely used by smart phones and vehicles in urban environments. The site-specific unmodeled errors mainly refer to the multipath and other space loss caused by the signal propagation (e.g., non-line-of-sight reception). As usual, the observation precisions are estimated by the weighting function in a stochastic model. Only once the realistic weighting function is applied can we obtain the precise positioning results. Unfortunately, the existing weighting schemes do not fully take these site-specific unmodeled effects into account. Specifically, the traditional weighting models indirectly and partly reflect, or even simply ignore, these unmodeled effects. In this paper, we propose a real-time adaptive weighting model to mitigate the site-specific unmodeled errors of code observations. This unmodeled-error-weighted model takes full advantages of satellite elevation angle and carrier-to-noise power density ratio (C/N0). In detail, elevation is taken as a fundamental part of the proposed model, then C/N0 is applied to estimate the precision of site-specific unmodeled errors. The principle of the second part is that the measured C/N0 will deviate from the nominal values when the signal distortions are severe. Specifically, the template functions of C/N0 and its precision, which can estimate the nominal values, are applied to adaptively adjust the precision of site-specific unmodeled errors. The proposed method is tested in single-point positioning (SPP) and code real-time differenced (RTD) positioning by static and kinematic datasets. Results indicate that the adaptive model is superior to the equal-weight, elevation and C/N0 models. Compared with these traditional approaches, the accuracy of SPP and RTD solutions are improved by 35.1% and 17.6% on average in the dense high-rise building group, as well as 11.4% and 11.9% on average in the urban-forested area. This demonstrates the benefit to code-based positioning brought by a real-time adaptive weighting model as it can mitigate the impacts of site-specific unmodeled errors and improve the positioning accuracy.

show abstract

Section: Of 18mentioning

confidence: 99%

Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

Shen

Gao

et al. 2018

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…1). Several numerical methods exist to solve velocity gradient tensor, e.g., Delaunay triangulation (Calais et al 2002), or statistical selection of homogeneous field (Pietrantonio and Riguzzi 2004); here, we used a regularly spaced gridded interpolation, with the distance weighted approach (Shen et al 1996;Allmendinger et al 2007;Cardozo and Allmendinger 2009). We constructed a uniform grid (5 9 5 km) in the area of the investigations (i.e., southern Tyrrhenian Sea and surroundings), and we estimated strain and rotation rate components at the center of each cell, using all the GPS velocities.…”

Section: Gps Data Processing and Strain Rate Field Analysismentioning

confidence: 99%

Coexisting tectonic settings: the example of the southern Tyrrhenian Sea

Cuffaro

Riguzzi

Scrocca

et al. 2011

Int J Earth Sci (Geol Rundsch)

View full text Add to dashboard Cite

We performed geodetic strain rate analyses in southern Italy, using new GPS velocities. Two-dimensional strain and rotation rate fields were estimated and results show that most of the shortening is distributed in the northern Sicily offshore. Extension becomes more evident and comparable with shortening on the eastern side of the same margin, and greater in the eastern Sicily offshore. Principal shortening and extension rate axes are consistent with long-term geological features: seismic reflection profiles show both active compressive and extensional faults affecting Pleistocene strata. We show evidence for contemporaneous extension and transtension in the Cefalu Basin. Combining geodetic data and geological features point to the coexistence of independent geodynamic processes, i.e., the active E-W backarc spreading in the hangingwall of the Apennines subduction zone and shortening along the southern margin of the Tyrrhenian backarc basin operated by the NNW-motion of Africa relative to Eurasia

show abstract

“…The velocities of Area B are roughly convergent towards the 2002-2003 degassing area. The horizontal strain rate estimated by STRAINGPS software (Pietrantonio and Riguzzi 2004) of Area B is shown in Fig. 2d.…”

Section: Velocity and Strain Rate Fieldsmentioning

confidence: 99%

Modeling ground deformations of Panarea volcano hydrothermal/geothermal system (Aeolian Islands, Italy) from GPS data

et al. 2010

View full text Add to dashboard Cite

Panarea volcano (Aeolian Islands, Italy) was \ud considered extinct until November 3, 2002, when a \ud submarine gas eruption began in the area of the islets of \ud Lisca Bianca, Bottaro, Lisca Nera, Dattilo, and Panarelli, \ud about 2.5 km east of Panarea Island. The gas eruption \ud decreased to a state of low degassing by July 2003. Before \ud 2002, the activity of Panarea volcano was characterized by \ud mild degassing of hydrothermal fluid. The compositions of \ud the 2002 gases and their isotopic signatures suggested that \ud the emissions originated from a hydrothermal/geothermal \ud reservoir fed by magmatic fluids. We investigate crustal \ud deformation of Panarea volcano using the global position- \ud ing system (GPS) velocity field obtained by the combina- \ud tion of continuous and episodic site observations of the \ud Panarea GPS network in the time span 1995–2007. We \ud present a combined model of Okada sources, which \ud explai ns the GPS results acquired in the area from \ud December 2002. The kinematics of Panarea volcano show \ud two distinct active crustal domains characterized by \ud different styles of horizontal deformation, supported also \ud by volcanological and structural evidence. Subsidence on \ud order of several millimeters/year is affecting the entire \ud Panarea volcano, and a shortening of 10−6 year−1 has been estimated in the Islets area. Our model reveals that the \ud degassing intensity and distribution are strongly influenced by \ud geophysical-geochemical changes within the hydrothermal/ \ud geothermal system. These variations may be triggered by \ud changes in the regional stress field as suggested by the \ud geophysical and volcanological events which occurred in \ud 2002 in the Southern Tyrrhenian area

show abstract

Three-dimensional strain tensor estimation by GPS observations: methodological aspects and geophysical applications

Cited by 48 publications

References 19 publications

Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

Coexisting tectonic settings: the example of the southern Tyrrhenian Sea

Modeling ground deformations of Panarea volcano hydrothermal/geothermal system (Aeolian Islands, Italy) from GPS data

Contact Info

Product

Resources

About