Subjects -> EARTH SCIENCES (Total: 771 journals)     - EARTH SCIENCES (527 journals)    - GEOLOGY (94 journals)    - GEOPHYSICS (33 journals)    - HYDROLOGY (29 journals)    - OCEANOGRAPHY (88 journals) EARTH SCIENCES (527 journals)                  1 2 3 | Last

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 Acta Geodaetica et GeophysicaJournal Prestige (SJR): 0.305 Citation Impact (citeScore): 1Number of Followers: 2      Hybrid journal (It can contain Open Access articles) ISSN (Print) 2213-5812 - ISSN (Online) 2213-5820 Published by Springer-Verlag  [2469 journals]
• A renewed view of basement structural geometry beneath the Southern Atlas
Front in Tunisia inferred from gravity, seismic reflection and earthquake
data

Abstract: The structural styles and origin of the southern Atlas Front of Tunisia have long been controversial, and a detailed geophysical analysis was performed in order to aid in deciphering the Precambrian basement structural geometry. Wavelength filtering produced a residual gravity anomaly map which indicated gravity maxima over the Sidi Mansour and Chott El-Fejej basins with the maxima being caused by basement uplifts. Upward continuation, 3D-Euler deconvolution and 2.5D gravity forward modeling indicated that the depths of Mesozoic units ranged up 3 to 4 km with the thickest Mesozoic sediments being in the Metlaoui-Gafsa and Chott El-Jerid basins. 2.5D gravity modeling constrained by seismic reflection profiles and well data indicated that the tectonic configuration of the Precambrian basement is dominated by grabens, half-grabens and horsts with the Sidi Mansour and El-Fejej basins being located on horsts. Gravity modeling shows the thinning of the basement from south to north and from east to west. Earthquake focal mechanisms and hypocenters suggest that the deepest faults are located in the basement, beneath the Metlaoui and Sidi Mansour basins. Additionally, a number of hypocenters occur within the Mesozoic sediments. These hypocenters, together with the faults imaged by the seismic reflection profiles, indicate that the structures in the northern part of the study area have been controlled by a mixture of thin- and thick-skinned tectonics. The reactivation of the basement faults including the east-trending faults formed during the Alpine orogeny by the current compressive stress regime has led to the inversion of the horst and graben structures.
PubDate: 2022-05-10

• Prediction of geoid undulation using approaches based on GMDH, M5 model
tree, MARS, GPR, and IDP

Abstract: Abstract This study provides a comprehensive comparison of four different machine learning models including the group method of data handling (GMDH), M5 model tree (M5MT), multivariate adaptive regression spline (MARS), and Gaussian process regression (GPR) for predicting geoid undulation. For the first time, GMDH and M5MT were applied for this purpose. The obtained results were also compared with the classic inverse distance to a power (IDP) interpolation method. In order to assess the consistency of our results, two test sites with different topographic features were used for the evaluation of the models. In constructing the models, the geographic coordinate values and the geoid undulation value were used as inputs and output, respectively. Several statistical indices and rank analysis were used for evaluation of the models. According to the comparative results of all models in both test sites, the GMDH yielded the best performance among the developed models. The M5MT also exhibited acceptable results. Thus, it may be concluded that the proposed GMDH and M5MT have the potential to be alternative models that could assist geoscientists working with the geoid.
PubDate: 2022-04-30

• Optimal selection of regularization parameter in magnetotelluric data
inversion

Abstract: Abstract Inversion of magnetotelluric data is known as a nonlinear and ill-posed problem. To obtain meaningful and unique results, Tikhonov's regularization method is commonly used to solve it. The optimal selection of the regularization parameter is another important factor for achieving an ideal inverse modeling. The aim of the present study is to find the optimal value for the regularization parameter in a two-dimensional inversion of magnetotelluric data by introducing a novel method. Furthermore, the Lanczos bidiagonalization method has been used to speed up the inversion process. For this purpose, three common methods including L-Curve, Generalized Cross-Validation, and Discrepancy Principle were investigated and then compared with the Adaptive Regularization as a novel optimal method in the inversion of 2D magnetotelluric data. All methods were provided as the Matlab code by authors. A 2D synthetic MT data with 3% random noise and Bushli (Nir) geothermal field MT data in Ardabil province, in the NW of Iran, was used by the introduced method for demonstrating its efficiency. The obtained results affirm that despite the capability of all methods in selecting the regularization parameter, the introduced method is more efficient than other conventional methods in terms of required memory, elapsed time, convergence to the desired model in fewer iterations, and modeling accuracy. Morever, applying this method on real data demonstrates its ability to generate a realistic inverted model.
PubDate: 2022-04-02

• Tikhonov-regularized weighted total least squares formulation with
applications to geodetic problems

Abstract: Abstract This contribution presents the Tikhonov regularized weighted total least squares (TRWTLS) solution in an errors-in-variables (EIV) model. The previous attempts had solved this problem based on the hybrid approximation solution (HAPS) within a nonlinear Gauss-Helmert model. The present formulation is a generalized form of the classical nonlinear Gauss-Helmert model, having formulated in an EIV general mixed observation model. It is a follow-up to the previous work throughout the WTLS problems formulated rely on a standard least squares (SLS) theory. Two cases, namely the EIV parametric model and the classical nonlinear mixed model, could be considered special cases of the general mixed observation model. These formulations are conceptually simple; because they are formulated based on the SLS theory, and subsequently, the existing SLS knowledge can directly be applied to the ill-posed mixed EIV model. Two geodetic applications have then adopted to illustrate the developed theory. As a first case, 2D affine transformation parameters (six-parameter affine transformation) for ill-scattered data points are adeptly solved by the TRWTLS method. Second, the circle fitting problem as a nonlinear case is not only tackled for well-scattered data points but also tackled for ill-scattered data points in a nonlinear mixed model. Finally, all results indicate that the Tikhonov regularization provides a stable and reliable solution in an ill-posed WTLS problem, and hence an efficient method applicable to many engineering problems.
PubDate: 2022-03-01
DOI: 10.1007/s40328-021-00365-1

• Determination of tectonic and crustal structure of Bitlis–Pötürge
Suture Zone using WGM2012 complete Bouguer anomaly data

Abstract: Abstract To investigate the crustal structure of the Bitlis–Pötürge Suture Zone and its vicinity, gravity complete Bouguer anomaly data obtained from the World Gravity Map (WGM2012) were analyzed using Spectral Depth Estimation, Frequency Filtering, Total Horizontal Derivative (THD) and Parker-Oldenburg inversion techniques. The THD method was applied to the data after band-pass filtering of Bouguer gravity data in order to image the discontinuities in the basement levels which are determined by the critical wave numbers determined from the amplitude spectrum of gravity complete Bouguer anomaly data. The maximum amplitude values of the THD were used to reveal the discontinuities caused by the density difference in the BPSZ and its vicinity. In addition, the basement upper surface topography of the region was calculated and mapped with the inverse solution. The presence of an uplift area that is an antiroot in the south of the study area, as well as the subsidence that is a root of the BPSZ was determined. As a result of the inverse solution, it was determined that the depth of the sedimentary basement in the south approximately reaches 6 km and was detected the presence of approximately 7 km thick sedimentary deposit on the BPSZ. Basement upper surface depth is calculated as 8 km in average under the Eastern Anatolian High Plateau.
PubDate: 2022-03-01
DOI: 10.1007/s40328-021-00353-5

• Extended WTLS iterative algorithm of 3D similarity transformation based on
Gibbs vector

Abstract: Abstract Considering coordinate errors of both control points and non-control points, and different weights between control points and non-control points, this contribution proposes an extended weighted total least squares (WTLS) iterative algorithm of 3D similarity transformation based on Gibbs vector. It treats the transformation parameters and the target coordinate of non-control points as unknowns. Thus it is able to recover the transformation parameters and compute the target coordinate of non-control points simultaneously. It is also able to assess the accuracy of the transformation parameters and the target coordinates of non-control points. Obviously it is different from the traditional algorithms that first recover the transformation parameters and then compute the target coordinate of non-control points by the estimated transformation parameters. Besides it utilizes a Gibbs vector to represent the rotation matrix. This representation does not introduce additional unknowns; neither introduces transcendental function like sine or cosine functions. As a result, the presented algorithm is not dependent to the initial value of transformation parameters. This excellent performance ensures the presented algorithm is suitable for the big rotation angles. Two numerical cases with big rotation angles including a real world case (LIDAR point cloud registration) and a simulative case are tested to validate the presented algorithm.
PubDate: 2022-03-01
DOI: 10.1007/s40328-021-00363-3

• A new ridge estimation method on rank-deficient adjustment model

Abstract: Abstract In this paper, we present a new ridge estimation method for solving rank-deficient least squares problems, in which a rank-deficient matrix is regarded as an almost rank-deficient. First, we give an algebraic derivation that the optimal solution can in fact be obtained by solving a related regularized problem on the optimal worst-case residual. Second, we give a new iterative algorithm to solve ridge parameter and prove its convergence. Finally, examples are given to demonstrate the efficiency of our new method. It is shown that the proposed algorithm can not only assess the stability of solution but also use additional prior information to guarantee the uniqueness of solutions to the problem of rank-deficient free-network adjustment.
PubDate: 2022-03-01
DOI: 10.1007/s40328-021-00366-0

• A method for updating GNSS satellite ultra-rapid clock offsets and orbits
with the aid of a covariance intersection algorithm

Abstract: Abstract Global navigation satellite system (GNSS) ultra-rapid clock offsets and orbit products are essential for near-real-time and real-time uses. To meet the requirements of accuracy and timeliness in high-accuracy applications, the issuing rates of ultra-rapid products are increased to six or three hours. However, there is an appreciable fluctuation of positioning residuals during the period of updating of products. To improve the performance of GNSS rapid services including the GPS, GLONASS, GALILEO and BeiDou, this paper proposes a method for updating satellite ultra-rapid clock offsets and orbits based on the covariance intersection algorithm, where kernel tricks are used to model the series in the position domain. Moreover, the parameter characteristics of the clock and orbit and the unknown inter-series correlation are considered in the model of satellite ultra-rapid products. Meanwhile, a sparse strategy is used in solving the model coefficients; i.e., the least absolute shrinkage and selection operator (LASSO) strategy. Several experimental schemes show that 1) jumps and gross errors in the GNSS ultra-rapid clock offset affect the modeling and services and should be detected and repaired before high-accuracy applications; 2) the updating of clock offsets and orbits reduces the steadiness of product services, while position residual fluctuations are introduced using GNSS precise point positioning solutions; 3) improved clock offset and orbit series can be obtained using the covariance intersection algorithm and kernel tricks; 4) the LASSO strategy can automatically and effectively choose and estimate the model coefficients of clock offset and orbit series; and 5) the proposed method can smooth the short-term arcs of GNSS products and positioning services by 29.8–99.5% for Multi-GNSS Experiment stations compared with original series. It is thus concluded that the proposed updating strategy is meaningful for improving GNSS satellite ultra-rapid products.
PubDate: 2022-02-16
DOI: 10.1007/s40328-022-00374-8

• Effects of high temperature on the linear thermal expansion coefficient of
Nanan granite

Abstract: Abstract The evaluation of physico-mechanical characteristics of rocks after thermal treatment is a key issue in underground rock engineering projects such as exploitation of geothermal resources and geological disposal of nuclear waste. In this research, the lengths of cylindrical Nanan granite specimens were obtained before, during and after thermal treatment (up to 1000 °C) to investigate their linear thermal expansion coefficients, and the variation mechanisms were revealed by optical microscopic observations. According to the experimental results collected from the extensive corresponding literature, the relationships between the linear thermal expansion coefficients of various granites were also elaborated. The experimental results demonstrated that the linear thermal expansion coefficients of the granite in this study both under and after thermal treatment increase with temperature. Meanwhile, the linear thermal expansion coefficients increase rapidly above 500 °C, which is because of the quartz phase transition from α–phase to β–phase. The increase of linear thermal expansion coefficients of granite under and after thermal treatment closely relates to the thermal expansion of mineral crystals and the development and coalescence of intergranular and transgranular microcracks. The experimental results are expected to provide a reference to analytical calculations of thermophysical processes in granite.
PubDate: 2022-02-07
DOI: 10.1007/s40328-022-00375-7

• Magnetotelluric resistivity imaging of the Baribis fault zone’s
Majalengka segment in West Java, Indonesia

Abstract: Abstract This work discusses the application of the magnetotelluric (MT) method to observing and delineating a local fault in the Majalengka Regency, West Java, Indonesia. This fault is part of the well-known Baribis fault segment. Phase tensor and induction vector analysis were applied to all MT data to reveal the dimensionality, geoelectric strike, and geological conditions of the study area, with 12 MT sites composing the studied profile. The estimated skew angle (β) value is − 3º < β < 3º enabling the subsurface structure modeling using the 2-D inversion. The calculated geoelectric strike of the study area of N15oE was used to rotate the impedance tensor of all MT observation points before modeling. The induction vector analysis revealed that the vectors did not lie in a particular direction. It can be possibly related to the volcanic products which dominate the surroundings of the study area. The 2-D subsurface electrical resistivity model suggested the presence of a very conductive zone (C1 ≤ 10 Ωm), which may be related to the existence of the targeted fault. The subsurface model also showed the resistivity contrasts between C1 (≤ 10 Ωm) and R1 (ρ ≥ 500 Ωm) as well as C1 (≤ 10 Ωm) and R2 (ρ = 50–100 Ωm). These notable contrasts are represented by the models’ block boundaries, and it is suggested that these may become a future earthquake epicenter.
PubDate: 2022-01-25
DOI: 10.1007/s40328-022-00372-w

• Ionospheric irregularities during disturbed geomagnetic conditions over
Argentinian EIA region

Abstract: Abstract Ionospheric irregularities can severely degrade radio communication and navigation systems. Geomagnetic storms may affect the generation of these irregularities in a way that is not yet fully understood. To improve the forecasting of this phenomenon, we need to study the ionosphere in different regions of the world, and in particular in the equatorial ionization anomaly (EIA) where irregularities are usually more intense. This study analyses the effect of geomagnetic storms on ionospheric irregularities. We examined the occurrence of irregularities at the southern crest of the EIA in Argentina (Tucumán, 26.9°S, 294.6°E, dip latitude 15.5°S) during three intense and one moderate geomagnetic storm of different solar sources, between 2015 and 2018. We used data from an ionosonde, a Global Positioning System receiver and magnetometers. Ionogram spread-F, the F-layer bottom side (h'F), the critical frequency of the F2-layer (foF2), the rate of TEC index and the S4 scintillation index were analysed. The data show irregularities were present as range spread-F and moderate TEC fluctuations in one storm: 27 May 2017 (a coronal mass ejection CME-driven storm occurred on local winter), and were absent in the other events. We suggest that eastward disturbance dynamo electric field and over-shielding prompt penetration electric fields may create favourable conditions for developing these irregularities, whereas westward storm time electric fields might inhibit the growth of irregularities during the other storms considered. During co-rotating interaction region CIR-driven storms, the westward disturbance dynamo electric field may be associated with the non-occurrence of irregularities.
PubDate: 2022-01-20
DOI: 10.1007/s40328-021-00370-4

• Magnetotelluric responses of a vertical inhomogeneous and anisotropic
resistivity structure with a transitional layer

Abstract: Abstract The theoretical magnetotelluric responses of a vertical inhomogeneous and anisotropic resistivity structure with a transitional layer in which the resistivity is a linear function of depth are investigated. The expressions of the tangential electric and magnetic fields at the surface of the Earth model and the corresponding impedance have been evaluated. The influence of some model parameters such as the anisotropic dipping angles, the anisotropic coefficients and the resistivity contrast as well as the thickness of the transitional layer on the apparent resistivity and impedance phase are treated in detail. The results are graphically illustrated in the form of apparent resistivity and impedance phase curves, and they may be used in the interpretation of magnetotelluric sounding data in some specified geologic situations.
PubDate: 2022-01-18
DOI: 10.1007/s40328-022-00373-9

• Gauss process regression for real-time ionospheric delay estimation from
GNSS observations

Abstract: Abstract The number of devices equipped with global satellite positioning has exceeded seven billion recently. There are a wide variety of receivers regarding their accuracy and reliability. Low cost, multi-frequency units have been released on the market latterly; however, the number of single-frequency receivers is still significant. Since their measurements are influenced by ionospheric delay, accurate ionosphere models are of utmost importance to reduce the effect. This paper summarizes how Gauss process regression (GPR) can be applied to derive near real-time regional ionosphere models using raw Global Navigation Satellite System (GNSS) observations of permanent stations. While Gauss process is widely used in machine learning, GPR is a nonparametric, Bayesian approach to regression. GPR has several benefits for ionosphere monitoring since it is quite robust and efficient to derive a grid model from data available in irregular set of ionospheric pierce points. The corresponding instrumental delays are estimated by a parallel Kalman filter. The presented algorithm can be applied near real-time, however the results are offline calculated and are compared to two high quality TEC map products. Based on the analysis, the accuracy of the GPR modell is in 2 TECu range. The developed methods could be efficiently applied in the field of autonomous vehicle navigation with meeting both accuracy and integrity requirements.
PubDate: 2022-01-12
DOI: 10.1007/s40328-021-00368-y

• Gauss process regression for real-time ionospheric delay estimation from
GNSS observations

Abstract: Abstract The number of devices equipped with global satellite positioning has exceeded seven billion recently. There are a wide variety of receivers regarding their accuracy and reliability. Low cost, multi-frequency units have been released on the market latterly; however, the number of single-frequency receivers is still significant. Since their measurements are influenced by ionospheric delay, accurate ionosphere models are of utmost importance to reduce the effect. This paper summarizes how Gauss process regression (GPR) can be applied to derive near real-time regional ionosphere models using raw Global Navigation Satellite System (GNSS) observations of permanent stations. While Gauss process is widely used in machine learning, GPR is a nonparametric, Bayesian approach to regression. GPR has several benefits for ionosphere monitoring since it is quite robust and efficient to derive a grid model from data available in irregular set of ionospheric pierce points. The corresponding instrumental delays are estimated by a parallel Kalman filter. The presented algorithm can be applied near real-time, however the results are offline calculated and are compared to two high quality TEC map products. Based on the analysis, the accuracy of the GPR modell is in 2 TECu range. The developed methods could be efficiently applied in the field of autonomous vehicle navigation with meeting both accuracy and integrity requirements.
PubDate: 2022-01-12
DOI: 10.1007/s40328-021-00368-y

• Assessment of point-mass solutions for recovering water mass variations
from satellite gravimetry

Abstract: Abstract Previous studies have shown the feasibility of point-mass modellings for deriving terrestrial water storage (TWS) from the harmonic solutions of the Gravity Recovery And Climate Experiment (GRACE) mission at regional scales (e.g., Greenland and Antarctica). However, a thorough assessment of point-mass modelling approaches at the global and river basin levels is still necessary. Therefore, this study’s objective is to assess the implementation and performance of the point-mass modelling approaches based on simulations using as inputs the TWS from Global Land Data Assimilation System (GLDAS). First, the approximate solutions of Newton’s integral using the Taylor series expansion, such that the zeroth-order approximation is equivalent to the “original point-mass” (OPM) and the third-order approximation to the “improved point-mass” (IPM) modellings are presented. Second, numerical comparisons of the gravitational potential forwarded by the IPM and OPM are carried out at which both approaches show errors smaller than the GRACE uncertainties for the potential differences ( $$\sim 7.6\times 10^{-4}$$ $$\hbox {m}^2$$ / $$\hbox {s}^2$$ ). Nevertheless, the spatial patterns of the OPM’s errors still assemble the TWS’s spatial variations. Finally, simulations showed that considering OPM’s deviations from IPM improves the root-mean-square-difference (RMSD) of the inverted TWS up to 50% at the global and basin scales if the edge effects are neglected. After accounting for the edge effects, the IPM solution presented an RMSD of 6.44 mm with an enhancement of about only 20% regarding the OPM. Although the present study confirms the suitability of point-mass approaches for recovering TWS, further investigations regarding its advantages compared to GRACE spherical harmonic synthesis are still necessary.
PubDate: 2022-01-11
DOI: 10.1007/s40328-021-00369-x

• Assessment of point-mass solutions for recovering water mass variations
from satellite gravimetry

Abstract: Abstract Previous studies have shown the feasibility of point-mass modellings for deriving terrestrial water storage (TWS) from the harmonic solutions of the Gravity Recovery And Climate Experiment (GRACE) mission at regional scales (e.g., Greenland and Antarctica). However, a thorough assessment of point-mass modelling approaches at the global and river basin levels is still necessary. Therefore, this study’s objective is to assess the implementation and performance of the point-mass modelling approaches based on simulations using as inputs the TWS from Global Land Data Assimilation System (GLDAS). First, the approximate solutions of Newton’s integral using the Taylor series expansion, such that the zeroth-order approximation is equivalent to the “original point-mass” (OPM) and the third-order approximation to the “improved point-mass” (IPM) modellings are presented. Second, numerical comparisons of the gravitational potential forwarded by the IPM and OPM are carried out at which both approaches show errors smaller than the GRACE uncertainties for the potential differences ( $$\sim 7.6\times 10^{-4}$$ $$\hbox {m}^2$$ / $$\hbox {s}^2$$ ). Nevertheless, the spatial patterns of the OPM’s errors still assemble the TWS’s spatial variations. Finally, simulations showed that considering OPM’s deviations from IPM improves the root-mean-square-difference (RMSD) of the inverted TWS up to 50% at the global and basin scales if the edge effects are neglected. After accounting for the edge effects, the IPM solution presented an RMSD of 6.44 mm with an enhancement of about only 20% regarding the OPM. Although the present study confirms the suitability of point-mass approaches for recovering TWS, further investigations regarding its advantages compared to GRACE spherical harmonic synthesis are still necessary.
PubDate: 2022-01-11
DOI: 10.1007/s40328-021-00369-x

• Comparisons of autoregressive integrated moving average (ARIMA) and long
short term memory (LSTM) network models for ionospheric anomalies
detection: a study on Haiti (Mw = 7.0) earthquake

Abstract: Abstract Since ionospheric variability changes dramatically before the major earthquakes (EQ), the detection of ionospheric anomalies for EQ forecasting has been a hot topic for modern-day researchers for the last couple of decades. Therefore, there is a need to identify highly accurate, advance, and intelligent models to identify these anomalies. In the present study, we have discussed artificial intelligence techniques e.g. autoregressive integrated moving average (ARIMA), and long short-term memory (LSTM) network, to detect ionospheric anomalies using the total electron content (TEC) time series over the epicenter of Mw 7.0 Haiti EQ on January 12, 2010. We have considered 20 days of TEC data with a daily 2-h interval and trained the models with an accuracy of 1.28 and 0.07 TECU for ARIMA and LSTM, respectively. Both ARIMA and LSTM results showed that the negative anomalies are recorded 5 days before the EQ (January 7), while strong positive anomalies are recorded 1–2 days before the EQ (January 11–12) that are consistent with the findings of previous studies. Moreover, the quiet space weather conditions during the analyzed period indicate that the observed variations could be considered precursors to the impending Haiti EQ. Our analysis suggests that the performance of the LSTM model is more robust as compared to the ARIMA model in terms of detection of seismoionospheric anomalies.
PubDate: 2022-01-11
DOI: 10.1007/s40328-021-00371-3

• Differences and similarities between precipitation patterns of different
climates

Abstract: Abstract In recent years water-related issues are increasing globally, some researchers even argue that the global hydrological cycle is accelerating, while the number of meteorological extremities is growing. With the help of large number of available measured data, these changes can be examined with advanced mathematical methods. In the outlined research we were able to collect long precipitation datasets from two different climatical regions, one sample area being Ecuador, the other one being Kenya. Using the methodology of spectral analysis based on the discrete Fourier-transformation, several deterministic components were calculated locally in the otherwise stochastic time series, while by the comparison of the results, also with previous calculations from Hungary, several global precipitation cycles were defined in the time interval between 1980 and 2019. The results of these calculations, the described local, regional, and global precipitation cycles can be a helpful tool for groundwater management, as precipitation is the major resource of groundwater recharge, as well as with the help of these deterministic cycles, precipitation forecasts can be delivered for the areas.
PubDate: 2021-12-01
DOI: 10.1007/s40328-021-00360-6

• Histogram-based weighted median filtering used for noise reduction of
digital elevation model data

Abstract: Abstract A new histogram-based robust filter developed for noise reduction of digital elevation model data is presented. When large percentage of data points in data matrices are contaminated with outlier noise, the noise reduction process can give better results than traditional median filtering, if elements with a potentially higher chance of being noise are eliminated by weighting from the input dataset before the median value is calculated. However, on the same matrices, there are likely to be subsets of data where unfiltered input is more reasonable for the calculation. The new method implementing weighting between these two cases is presented below, with its initial tuning and a comparison with both standard median filtering and the Most Frequent Value (MFV) method, as the latter being much more efficient than the usual methods. Following the description of the procedures, their effectiveness is compared for noise reduction in digital elevation model data systems, at various noise levels. The comparison is done mainly by three measures, with most of the focus on the $${L}_{1}$$ norm data distance results. Finally, a modified version of the method—which includes Steiner’s MFV filter as a core part—is also introduced, with similar examination. The method to be presented has been shown to be superior to conventional median filtering for most noise rates, and in many cases also to Steiner' MFV, for handling non-zero mean noises. The modified version of the method—with the help of Steiner's MFV—has also achieved this in handling zero mean noise, in the field of application described in the paper.
PubDate: 2021-12-01
DOI: 10.1007/s40328-021-00356-2

• An MFV-based image processing filter and its application to seismic
tomographic images

Abstract: Abstract In the tomographic reconstruction of seismic travel time data, care must be taken to keep the propagation of data errors to the model space under control. The non-Gaussian noise distribution—especially the outliers in the data sets- can cause appreciable distortions in the tomographic imaging. To reduce the noise sensitivity well-developed tomography algorithms can be used. On the other hand, the quality of the tomogram can further be improved by using image processing tools. In the paper, a newly developed robust filter is presented, in which the Most Frequent Value (MFV) method developed by Steiner is applied. To analyze the noise reduction capability of the new filter (called Steiner-filter) and to compare it to smoothing filters based on arithmetic- and binomial mean, as well as median, medium-sized tomographic images are used. The MFV-based filter is successfully tested also in edge detection procedures.
PubDate: 2021-12-01
DOI: 10.1007/s40328-021-00351-7

• Machine learning based approach for the interpretation of engineering
geophysical sounding logs

Abstract: Abstract In this paper, a set of machine learning (ML) tools is applied to estimate the water saturation of shallow unconsolidated sediments at the Bátaapáti site in Hungary. Water saturation is directly calculated from the first factor extracted from a set of direct push logs by factor analysis. The dataset observed by engineering geophysical sounding tools as special variants of direct-push probes contains data from a total of 12 shallow penetration holes. Both one- and two-dimensional applications of the suggested method are presented. To improve the performance of factor analysis, particle swarm optimization (PSO) is applied to give a globally optimized estimate for the factor scores. Furthermore, by a hyperparameter estimation approach, some control parameters of the utilized PSO algorithm are automatically estimated by simulated annealing (SA) to ensure the convergence of the procedure. The result of the suggested ML-based log analysis method is compared and verified by an independent inversion estimate. The study shows that the PSO-based factor analysis aided by hyperparameter estimation provides reliable in situ estimates of water saturation, which may improve the solution of environmental end engineering problems in shallow unconsolidated heterogeneous formations.
PubDate: 2021-12-01
DOI: 10.1007/s40328-021-00354-4

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