A priori noise and regularization in least squares collocation of gravity anomalies

2013 ◽  
Vol 62 (2) ◽  
pp. 199-216 ◽  
Author(s):  
Wojciech Jarmołowski
Keyword(s):  
Least Squares ◽  
Spatial Resolution ◽  
Gravity Data ◽  
A Priori ◽  
Gravity Anomalies ◽  
Geopotential Model ◽  
Large Set ◽  
Least Squares Collocation ◽  
Gravity Field Model ◽  
Two Parameters

Abstract The paper describes the estimation of covariance parameters in least squares collocation (LSC) by the cross-validation (CV) technique called leave-one-out (LOO). Two parameters of Gauss-Markov third order model (GM3) are estimated together with a priori noise standard deviation, which contributes significantly to the covariance matrix composed of the signal and noise. Numerical tests are performed using large set of Bouguer gravity anomalies located in the central part of the U.S. Around 103 000 gravity stations are available in the selected area. This dataset, together with regular grids generated from EGM2008 geopotential model, give an opportunity to work with various spatial resolutions of the data and heterogeneous variances of the signal and noise. This plays a crucial role in the numerical investigations, because the spatial resolution of the gravity data determines the number of gravity details that we may observe and model. This establishes a relation between the spatial resolution of the data and the resolution of the gravity field model. This relation is inspected in the article and compared to the regularization problem occurring frequently in data modeling.

scholarly journals Estimation of gravity noise variance and signal covariance parameters in least squares collocation with considering data resolution

2016 ◽  
Vol 59 (1) ◽  
Author(s):  
Wojciech Jarmołowski
Keyword(s):  
Least Squares ◽  
Likelihood Function ◽  
A Priori ◽  
Gravity Anomalies ◽  
Signal Spectrum ◽  
Noise Variance ◽  
Covariance Model ◽  
Least Squares Collocation ◽  
Uncorrelated Noise ◽  
Data Resolution

<p>The article describes an implementation of the negative log-likelihood function in the determination of uncorrelated noise standard deviation together with the parameters of spherical signal covariance model in least squares collocation (LSC) of gravity anomalies. The correctness and effectiveness of restricted maximum likelihood (REML) estimates are fully validated by leave-one-out validation (LOO). These two complementary methods give an opportunity to inspect the parametrization of the signal and uncorrelated noise in details and can provide some guidance related to the estimation of individual parameters. The study provides the practical proof that noise variance is related with the data resolution, which is often neglected and the information on a priori noise variance is based on the measurement error. The data have been downloaded from U.S. terrestrial gravity database and resampled to enable an analysis with four different horizontal resolutions. These data are intentionally the same, as in the previous study of the same author, with the application of the planar covariance model. The aim is to compare the results from two different covariance models, which have different covariance approximation at larger distances. The most interesting outputs from this study confirm previous observations on the relations of the data resolution, a priori noise variance, signal spectrum and LSC accuracy.</p>

scholarly journals Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test area

2012 ◽  
Vol 2 (1) ◽  
pp. 53-64 ◽  
Author(s):  
H. Yildiz ◽  
R. Forsberg ◽  
J. Ågren ◽  
C. Tscherning ◽  
L. Sjöberg
Keyword(s):  
Least Squares ◽  
Gravity Data ◽  
Test Area ◽  
Geoid Determination ◽  
Geopotential Model ◽  
Low Degree ◽  
Residual Terrain Modelling ◽  
The Alps ◽  
Stokes Formula ◽  
Regional Geoid Determination

Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test areaThe remove-compute-restore (RCR) technique for regional geoid determination implies that both topography and low-degree global geopotential model signals are removed before computation and restored after Stokes' integration or Least Squares Collocation (LSC) solution. The Least Squares Modification of Stokes' Formula (LSMS) technique not requiring gravity reductions is implemented here with a Residual Terrain Modelling based interpolation of gravity data. The 2-D Spherical Fast Fourier Transform (FFT) and the LSC methods applying the RCR technique and the LSMS method are tested over the Auvergne test area. All methods showed a reasonable agreement with GPS-levelling data, in the order of a 3-3.5 cm in the central region having relatively smooth topography, which is consistent with the accuracies of GPS and levelling. When a 1-parameter fit is used, the FFT method using kernel modification performs best with 3.0 cm r.m.s difference with GPS-levelling while the LSMS method gives the best agreement with GPS-levelling with 2.4 cm r.m.s after a 4-parameter fit is used. However, the quasi-geoid models derived using two techniques differed from each other up to 33 cm in the high mountains near the Alps. Comparison of quasi-geoid models with EGM2008 showed that the LSMS method agreed best in term of r.m.s.

scholarly journals Polar motion from ILS observations with least-squares collocation

1988 ◽  
Vol 128 ◽  
pp. 215-220
Author(s):  
R. Verbeiren
Keyword(s):  
Least Squares ◽  
Observational Data ◽  
Polar Motion ◽  
Parameter Determination ◽  
Large Set ◽  
Powerful Method ◽  
Least Squares Collocation ◽  
Computational Step

Least-squares collocation is a powerful method for combining interpolation, filtering and parameter determination in one single computational step. We show that the method is applicable to the computation of polar motion values from a very large set of basic observational data. In this study, we use the ILS observations from 1900 to 1978.

scholarly journals Basement Mapping of the Fucino Basin in Central Italy by ITRESC Modeling of Gravity Data

Geosciences ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 398
Author(s):  
Federico Cella ◽  
Rosa Nappi ◽  
Valeria Paoletti ◽  
Giovanni Florio
Keyword(s):  
Seismic Activity ◽  
Site Response ◽  
Gravity Data ◽  
A Priori ◽  
Central Italy ◽  
Gravity Anomalies ◽  
Gravity Modeling ◽  
Ground Shaking ◽  
Sedimentary Evolution ◽  
Fucino Basin

Sediments infilling in intermontane basins in areas with high seismic activity can strongly affect ground-shaking phenomena at the surface. Estimates of thickness and density distribution within these basin infills are crucial for ground motion amplification analysis, especially where demographic growth in human settlements has implied increasing seismic risk. We employed a 3D gravity modeling technique (ITerative RESCaling—ITRESC) to investigate the Fucino Basin (Apennines, central Italy), a half-graben basin in which intense seismic activity has recently occurred. For the first time in this region, a 3D model of the Meso-Cenozoic carbonate basement morphology was retrieved through the inversion of gravity data. Taking advantage of the ITRESC technique, (1) we were able to (1) perform an integration of geophysical and geological data constraints and (2) determine a density contrast function through a data-driven process. Thus, we avoided assuming a priori information. Finally, we provided a model that honored the gravity anomalies field by integrating many different kinds of depth constraints. Our results confirmed evidence from previous studies concerning the overall shape of the basin; however, we also highlighted several local discrepancies, such as: (a) the position of several fault lines, (b) the position of the main depocenter, and (c) the isopach map. We also pointed out the existence of a new, unknown fault, and of new features concerning known faults. All of these elements provided useful contributions to the study of the tectono-sedimentary evolution of the basin, as well as key information for assessing the local site-response effects, in terms of seismic hazards.

scholarly journals A High-Resolution Gravimetric Geoid Model for Kuwait Using the Least-Squares Collocation

2022 ◽  
Vol 9 ◽  
Author(s):  
Hamad Al-Ajami ◽  
Ahmed Zaki ◽  
Mostafa Rabah ◽  
Mohamed El-Ashquer
Keyword(s):  
High Resolution ◽  
Least Squares ◽  
Geopotential Model ◽  
Gravimetric Geoid ◽  
Least Squares Collocation ◽  
Geoid Model ◽  
Terrestrial Gravity ◽  
Digital Elevation ◽  
Elevation Model ◽  
Gps Leveling

A new gravimetric geoid model, the KW-FLGM2021, is developed for Kuwait in this study. This new geoid model is driven by a combination of the XGM2019e-combined global geopotential model (GGM), terrestrial gravity, and the SRTM 3 global digital elevation model with a spatial resolution of three arc seconds. The KW-FLGM2021 has been computed by using the technique of Least Squares Collocation (LSC) with Remove-Compute-Restore (RCR) procedure. To evaluate the external accuracy of the KW-FLGM2021 gravimetric geoid model, GPS/leveling data were used. As a result of this evaluation, the residual of geoid heights obtained from the KW-FLGM2021 geoid model is 2.2 cm. The KW-FLGM2021 is possible to be recommended as the first accurate geoid model for Kuwait.

Towards an updated, enhanced regional gravity field solution for Antarctica

2021 ◽  
Author(s):  
Mirko Scheinert ◽  
Philipp Zingerle ◽  
Theresa Schaller ◽  
Roland Pail ◽  
Martin Willberg
Keyword(s):  
Gravity Anomaly ◽  
Gravity Field ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Data Set ◽  
Gravity Field Model ◽  
Terrestrial Gravity ◽  
Field Solution ◽  
Gravity Disturbances ◽  
Regional Gravity

&lt;p&gt;In the frame of the IAG Subcommission 2.4f &amp;#8220;Gravity and Geoid in Antarctica&amp;#8221; (AntGG) a first Antarctic-wide grid of ground-based gravity anomalies was released in 2016 (Scheinert et al. 2016). That data set was provided with a grid space of 10 km and covered about 73% of the Antarctic continent. Since then a considerably amount of new data has been made available, mainly collected by means of airborne gravimetry. Regions which were formerly void of any terrestrial gravity observations and have now been surveyed include especially the polar data gap originating from GOCE satellite gravimetry. Thus, it is timely to come up with an updated and enhanced regional gravity field solution for Antarctica. For this, we aim to improve further aspects in comparison to the AntGG 2016 solution: The grid spacing will be enhanced to 5 km. Instead of providing gravity anomalies only for parts of Antarctica, now the entire continent should be covered. In addition to the gravity anomaly also a regional geoid solution should be provided along with further desirable functionals (e.g. gravity anomaly vs. disturbance, different height levels).&lt;/p&gt;&lt;p&gt;We will discuss the expanded AntGG data base which now includes terrestrial gravity data from Antarctic surveys conducted over the past 40 years. The methodology applied in the analysis is based on the remove-compute-restore technique. Here we utilize the newly developed combined spherical-harmonic gravity field model SATOP1 (Zingerle et al. 2019) which is based on the global satellite-only model GOCO05s and the high-resolution topographic model EARTH2014. We will demonstrate the feasibility to adequately reduce the original gravity data and, thus, to also cross-validate and evaluate the accuracy of the data especially where different data set overlap. For the compute step the recently developed partition-enhanced least-squares collocation (PE-LSC) has been used (Zingerle et al. 2021, in review; cf. the contribution of Zingerle et al. in the same session). This method allows to treat all data available in Antarctica in one single computation step in an efficient and fast way. Thus, it becomes feasible to iterate the computations within short time once any input data or parameters are changed, and to easily predict the desirable functionals also in regions void of terrestrial measurements as well as at any height level (e.g. gravity anomalies at the surface or gravity disturbances at constant height).&lt;/p&gt;&lt;p&gt;We will discuss the results and give an outlook on the data products which shall be finally provided to present the new regional gravity field solution for Antarctica. Furthermore, implications for further applications will be discussed e.g. with respect to geophysical modelling of the Earth&amp;#8217;s interior (cf. the contribution of Schaller et al. in session G4.3).&lt;/p&gt;

Shape and depth solutions from gravity data using correlation factors between successive least‐squares residuals

Geophysics ◽  
1993 ◽  
Vol 58 (12) ◽  
pp. 1785-1791 ◽  
Author(s):  
El‐Sayed M. Abdelrahman ◽  
Hesham M. El‐Araby
Keyword(s):  
Least Squares ◽  
Shape Factor ◽  
Gravity Data ◽  
Bouguer Anomaly ◽  
Vertical Cylinder ◽  
Gravity Anomalies ◽  
Horizontal Cylinder ◽  
Amplitude Coefficient ◽  
Regional Component ◽  
Correlation Factors

The gravity anomaly expression produced by most geologic structures can be represented by a continuous function in both shape (shape factor) and depth variables with an amplitude coefficient related to the mass. Correlation factors between successive least‐squares residual gravity anomalies from a buried vertical cylinder, horizontal cylinder, and sphere are used to determine the shape and depth of the buried geologic structure. For each shape factor value, the depth is determined automatically from the correlation value. The computed depths are plotted against the shape factor representing a continuous correlation curve. The solution for the shape and depth of the buried structure is read at the common intersection of correlation curves. This method can be applied to a Bouguer anomaly profile consisting of a residual component caused by local structure and a regional component. This is a powerful technique for automatically separating the Bouguer data into residual and regional polynomial components. This method is tested on theoretical examples and a field example. In both cases, the results obtained are in good agreement with drilling results.

Prediction of Deviations of the Vertical Using Heterogeneous Data

1976 ◽  
Vol 30 (2) ◽  
pp. 97-108
Author(s):  
Gérard Lachapelle
Keyword(s):  
Least Squares ◽  
Gravity Anomalies ◽  
Heterogeneous Data ◽  
Numerical Results ◽  
Geodetic Data ◽  
West Germany ◽  
Mountainous Areas ◽  
Least Squares Collocation ◽  
Dynamic Information ◽  
Geopotential Coefficients

A method for estimating deviations of the vertical from a combination of topographic-isostatic deviations of the vertical and dynamic information in the form of geopotential coefficients is presented. The method is especially well suited for large areas, either continental or oceanic, where no geodetic measurements, such as gravity anomalies or deviations of the vertical, are available. It is ideally applicable in mountainous areas and along coastlines where the deviations depend greatly on the topography. Numerical results using topographic-isostatic data calculated in Canada, Switzerland and West Germany are presented. Furthermore, if geodetic data such as observed deviations of the vertical and gravity anomalies are available in the area considered, they can be combined with existing estimated deviations by using least squares collocation to achieve a greater accuracy.

BOUGUER GRAVITY CORRECTIONS USING A VARIABLE DENSITY

Geophysics ◽  
1962 ◽  
Vol 27 (5) ◽  
pp. 616-626 ◽  
Author(s):  
F. S. Grant ◽  
A. F. Elsaharty
Keyword(s):  
Least Squares ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Variable Density ◽  
Bouguer Gravity ◽  
Method Of Least Squares ◽  
Surface Conditions ◽  
Worked Example ◽  
Local Gravity

The principle of density profiling as a means of determining Bouguer densities is studied with a view to extending it to include all of the data in a survey. It is regarded as an endeavor to minimize the correlation between local gravity anomalies and topography, and as such it can be handled mathematically by the method of least squares. In the general case this leads to a variable Bouguer density which can be mapped and contoured. In a worked example, the correspondence between this function and the known geology appears to be good, and indicates that Bouguer density variations due to changing surface conditions can be used routinely in the reduction of gravity data.

A least‐squares minimization approach to depth determination from moving average residual gravity anomalies

Geophysics ◽  
1993 ◽  
Vol 58 (12) ◽  
pp. 1779-1784 ◽  
Author(s):  
El‐Sayed M. Abdelrahman ◽  
Tarek M. El‐Araby
Keyword(s):  
Least Squares ◽  
Gravity Data ◽  
Moving Average ◽  
Gravity Anomalies ◽  
The United States ◽  
Random Errors ◽  
Minimization Method ◽  
Residual Gravity ◽  
Average Residual ◽  
Least Squares Minimization

We have developed a least‐squares minimization method to estimate the depth of a buried structure from moving average residual gravity anomalies. The method involves fitting simple models convolved with the same moving average filter as applied to the observed gravity data. As a result, our method can be applied not only to residuals but also to the Bouguer gravity data of a short profile length. The method is applied to synthetic data with and without random errors. The validity of the method is tested in detail on two field examples from the United States and Senegal.

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