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Abstract Grain Size Distribution is one of the basic measurements for sediment classification. The conventional methods for grain size distribution include the sieve method, the laser diffraction method, and the point-count method. We aimed to develop a robust computer code that simulates these conventional methods. The code can measure grain size distribution on 2-D and 3-D binary images using a watershed algorithm to extract out individual grains, and using principal component algorithms to find the principal axes. The outputs include grain radius for different principal axes, grain volume, grain surface area, principal axes inclinations and azimuths, and the number of contacts for each grain. The calculated distribution can be volume-based, frequency-based, or grid-based. Digital microstructures used in this study include (1) identical sphere packs including a simple cubic pack and a Finney pack, and (2) natural rock geometry such as Berea sandstone, Castlegate sandstone, and Fontainebleau sandstone. Furthermore, we employed this code to provide additional value of information from μXCT images by using μXCT to create 2-D to 3-D model of the grain size distribution, solving what is commonly known as Wicksell's corpuscle problem. We showed that our workflow successfully models a generalized 2-D to 3-D grain size distribution for a particular set of natural rocks that we include in our study. We hope to be able to obtain more μXCT images in the future in order to create a universal model covering most types of natural rocks. Highlights • Robust codes to measure grain size distribution from thin-sections or μXCT images. • Distribution based on sieve method, laser diffraction method, and point-count method. • Model a generalized 2-D to 3-D grain size distributions. [ABSTRACT FROM AUTHOR]

Modelling wave propagation is the most essential part in assessing the risk and hazard of tsunami and storm surge events. For the computational assessment of the variability of such events, many simulations are necessary. Even today, most of these simulations are generally run on supercomputers due to the large amount of computations necessary. In this study, a simulation framework, named TsuPy, is introduced to quickly compute tsunami events on a personal computer. It uses the parallelized power of GPUs to accelerate computation. The system is tailored to the application of robust tsunami hazard and risk modelling. It links up to geophysical models to simulate event sources. The system is tested and validated using various benchmarks and real-world case studies. In addition, the robustness criterion is assessed based on a sensitivity study comparing the error impact of various model elements e.g. of topo-bathymetric resolution, knowledge of Manning friction parameters and the knowledge of the tsunami source itself. This sensitivity study is tested on inundation modelling of the 2011 Tohoku tsunami, showing that the major contributor to model uncertainty is in fact the representation of earthquake slip as part of the tsunami source profile. TsuPy provides a fast and reliable tool to quickly assess ocean hazards from tsunamis and thus builds the foundation for a globally uniform hazard and risk assessment for tsunamis. [ABSTRACT FROM AUTHOR]

Glacier reconstructions are widely used in palaeoclimatic studies and this paper presents a new semi-automated method for generating glacier reconstructions: GlaRe, is a toolbox coded in Python and operating in ArcGIS. This toolbox provides tools to generate the ice thickness from the bed topography along a palaeoglacier flowline applying the standard flow law for ice, and generates the 3D surface of the palaeoglacier using multiple interpolation methods. The toolbox performance has been evaluated using two extant glaciers, an icefield and a cirque/valley glacier from which the subglacial topography is known, using the basic reconstruction routine in GlaRe. Results in terms of ice surface, ice extent and equilibrium line altitude show excellent agreement that confirms the robustness of this procedure in the reconstruction of palaeoglaciers from glacial landforms such as frontal moraines. [ABSTRACT FROM AUTHOR]

Governments and companies around the world collect point clouds (datasets containing elevation points) because these are useful for many applications, e.g. to reconstruct 3D city models, to understand and predict the impact of floods, and to monitor dikes. We address in this paper the visualisation of point clouds, which is perhaps the most essential instrument a practitioner or a scientist has to analyse and understand such datasets. We argue that it is currently hampered by two main problems: (1) point clouds are often massive (several billion points); (2) the viewer's perception of depth and structure is often lost (because of the sparse and unstructured points). We propose solving both problems by using the Medial Axis Transform (MAT) and its properties. This allows us to (1) smartly simplify a point cloud in a geometry-dependent way (to preserve only significant features), and (2) to render splats whose radii are adaptive to the distribution of points (and thus obtain less “holes” in the surface). Our main contribution is a series of heuristics that allows us to compute the MAT robustly for noisy real-world LiDAR point clouds, and to compute the MAT for point clouds that do not fit into the main memory. We have implemented our algorithms, we report on experiments made with point clouds (of more than one billion points), and we demonstrate that we are able to render scenes with much less points than in the original point cloud (we preserve around 10%) while retaining good depth-perception and a sense of structure at close viewing distances. [ABSTRACT FROM AUTHOR]

This paper presents an automated discontinuity trace mapping method on a 3D surface model of rock mass. Feature points of discontinuity traces are first detected using the Normal Tensor Voting Theory, which is robust to noisy point cloud data. Discontinuity traces are then extracted from feature points in four steps: (1) trace feature point grouping, (2) trace segment growth, (3) trace segment connection, and (4) redundant trace segment removal. A sensitivity analysis is conducted to identify optimal values for the parameters used in the proposed method. The optimal triangular mesh element size is between 5 cm and 6 cm; the angle threshold in the trace segment growth step is between 70° and 90°; the angle threshold in the trace segment connection step is between 50° and 70°, and the distance threshold should be at least 15 times the mean triangular mesh element size. The method is applied to the excavation face trace mapping of a drill-and-blast tunnel. The results show that the proposed discontinuity trace mapping method is fast and effective and could be used as a supplement to traditional direct measurement of discontinuity traces. [ABSTRACT FROM AUTHOR]

High performance computing is absolutely necessary for large-scale geophysical simulations. In order to obtain a realistic image of a geologically complex area, industrial surveys collect vast amounts of data making the computational cost extremely high for the subsequent simulations. A major computational bottleneck of modeling and inversion algorithms is solving the large sparse systems of linear ill-conditioned equations in complex domains with multiple right hand sides. Recently, parallel direct solvers have been successfully applied to multi-source seismic and electromagnetic problems. These methods are robust and exhibit good performance, but often require large amounts of memory and have limited scalability. In this paper, we evaluate modern direct solvers on large-scale modeling examples that previously were considered unachievable with these methods. Performance and scalability tests utilizing up to 65,536 cores on the Blue Waters supercomputer clearly illustrate the robustness, efficiency and competitiveness of direct solvers compared to iterative techniques. Wide use of direct methods utilizing modern parallel architectures will allow modeling tools to accurately support multi-source surveys and 3D data acquisition geometries, thus promoting a more efficient use of the electromagnetic methods in geophysics. [ABSTRACT FROM AUTHOR]

The selection of best management practices to reduce soil and water pollution often requires estimation of soil properties. It is important to find an efficient and robust technique to simulate spatially correlated soils parameters. Co-kriging and co-simulation are techniques that can be used. These methods are limited in terms of computer simulation due to the problem of solving large co-kriging systems and difficulties in fitting a valid model of coregionalization. The order of complexity increases as the number of covariables increases. This paper presents a technique for the conditional simulation of a non-Gaussian vector random field on point support scale. The technique is termed Independent Component Analysis (ICA). The basic principle underlining ICA is the determination of a linear representation of non-Gaussian data so that the components are considered statistically independent. With such representation, it would be easy and more computationally efficient to develop direct variograms for the components. The process is presented in two stages. The first stage involves the ICA decomposition. The second stage involves sequential Gaussian simulation of the generated components (which are derived from the first stage). This technique was applied for spatially correlated extractable cations such as magnesium (Mg) and iron (Fe) in a Canadian watershed. This paper has a strong application in stochastic quantification of uncertainties of soil attributes in soil remediation and soil rehabilitation. [ABSTRACT FROM AUTHOR]

Polyline simplification is an important task in map generalization. Several solutions have been developed in order to perform this task automatically, but the vast majority of them consider that the objective line to simplify is lying on the plane. One of the most widely used methods is the so-called Douglas–Peucker algorithm, which is fast and in most cases produces good results. However, the Douglas–Peucker method was defined in its original form in order to be applied to polylines contained in the Euclidean 2D space, and it can lead to inconsistent results such as self-intersections. In this work, a robust (results without self-intersections) variation of the Douglas–Peucker for polylines on the surface of the sphere is presented. It produces correct results regardless of the morphology of the original line and the tolerance parameter size. The algorithm is coded in standard C99 and it can be compiled for serial or parallel execution via OpenMP. Both, the algorithm itself and a program implementing it are distributed as free software. The solution validity was tested using the GSHHG geography database, which can be obtained free through the Web. Results about output accuracy, execution speed, and parallel implementation scalability are presented. [ABSTRACT FROM AUTHOR]

Subsurface processing numerical simulations require accurate discretization of the modeling domain such that the geological units are represented correctly. Unstructured tetrahedral grids are particularly flexible in adapting to the shape of geo-bodies and are used in many finite element codes. In order to generate a tetrahedral mesh on a 3D geological model, the tetrahedrons have to belong completely to one geological unit and have to describe geological boundaries by connected facets of tetrahedrons. This is especially complicated at the contact points between several units and for irregular sharp-shaped bodies, especially in case of faulted zones. This study develops, tests and validates three workflows to generate a good tetrahedral mesh from a geological basis model. The tessellation of the model needs (i) to be of good quality to guarantee a stable calculation, (ii) to include certain nodes to apply boundary conditions for the numerical solution, and (iii) support local mesh refinement. As a test case we use the simulation of a transient electromagnetic measurement above a salt diapir. We can show that the suggested workflows lead to a tessellation of the structure on which the simulation can be run robustly. All workflows show advantages and disadvantages with respect to the workload, the control the user has over the resulting mesh and the skills in software handling that are required. [ABSTRACT FROM AUTHOR]

Numerical models of geological structures are generally built with a geometrical approach, which lacks an explicit representation of the deformation history and may lead to incompatible structures. We advocate that the deformation history should be investigated and represented from the very first steps of the modelling process, provided that a series of rapid, interactive or automated, deformation tools are available for local editing, forward modelling and restoration. In this paper, we define the specifications of such tools and emphasise the need for rapidity and robustness. We briefly review the different applications of deformation tools in geomodelling and the existing deformation algorithms. We select a deformation algorithm based on rigid elements, first presented in the Computer Graphics community, which we refer to as Reed . It is able to rapidly deform any kind of geometrical object, including points, lines or volumes, with an approximated mechanical behaviour. The objects to be deformed are embedded in rigid cells whose displacement is optimised by minimising a global cost function with respect to displacement boundary conditions. This cost function measures the difference in displacement between neighbouring elements. The embedded objects are then deformed based on their original position with respect to the rigid elements. We present the basis of our implementation of this algorithm and highlight its ability to fulfil the specifications we defined. Its application to geomodelling specific problems is illustrated through the construction of a synthetic structural model of multiply deformed layers with a forward modelling approach. A special boundary condition adapted to restore large folds is also presented and applied to the large anticline of Han-sur-Lesse, Belgium, which demonstrates the ability of this method to efficiently perform a volumetric restoration without global projections. [ABSTRACT FROM AUTHOR]

Abstract: Curvature based methods are suitable for channel identification in digital elevation models. One obstacle in using these methods is the fact that channels generally occur at multiple scales in the landscape, from small creeks to large rivers. In this paper, we show how likely channel pixels can be identified simultaneously at a range of scales using multiscale curvature operators applied to digital elevation models. Our proposed Hyperscale Channel Extraction (HCE) method localizes channels at the smallest scale while simultaneously tracking the shape of the channel at a full interval of scales (the hyperscale). We test the method using two different types of curvature, and apply and validate it to a catchment representing terrain with a high slope sampled by airborne laser altimetry. The test results demonstrate that by explicitly employing the extra dimension of scale to localize channels, (a) we are able to robustly identify channel pixels, as possible channel locations are tracked through a full interval of scales, (b) no more a priori determination of the relevant scale is necessary, and (c) only one parameter remains to be set: a threshold on the curvature value that has a clear physical interpretation. [Copyright &y& Elsevier]

Abstract: The measurement of Very Low Frequency Electromagnetic (VLF-EM) is important in many different applications, i.e, environmental, archeological, geotechnical studies, etc. In recent years, improving and enhancing VLF-EM data containing complex numbers (bivariate) was presented by several authors in order to produce reliable models, generally using univariate empirical mode decomposition (EMD). Applying univariate EMD separately on each data is problematic. This results in a different number of misaligned Intrinsic Mode Functions (IMFs) which can complicate the selection of some IMFs for denoising process. Thus, a filtering method based on the multivariate empirical mode decomposition (MEMD) approach to decompose simultaneously bivariate data is proposed. In this paper we address two issues by employing the recently introduced noise assisted MEMD (N-A MEMD) for improving bivariate VLF-EM data. Firstly, the N-A MEMD to decompose bivariate measurement of the VLF-EM data into IMFs and a residue is defined as VLF-EM signal or unwanted noise. Secondly, the proposed method is used to enhance VLF-EM data and to reject unwanted noise. Finally, the proposed method is applied to a synthetic data with two added sinusoids. To demonstrate the robustness of the N-A MEMD method, the method was tested on added-noise synthetic data sets and the results were compared to the Ensemble EMD (EEMD) and Bivariate EMD (BEMD). The N-A MEMD gave more robust and accurate results than the EEMD and BEMD methods and the method required less CPU time to obtain the IMFs compared to EEMD. The method was also tested on several field data sets. The results indicate that the filtered VLF-EM data based on the N-A MEMD make the data easier to interpret and to be analyzed further. In addition, the 2D resistivity profile estimated from the inversion of filtered VLF-EM data results was appropriate to the geological condition. [Copyright &y& Elsevier]

Abstract: We review and give a practical example of Latin hypercube sampling in soil science using an approach we call flexible Latin hypercube sampling. Recent studies of soil properties in large and remote regions have highlighted problems with the conventional Latin hypercube sampling approach. It is often impractical to travel far from tracks and roads to collect samples, and survey planning should recognise this fact. Another problem is how to handle target sites that, for whatever reason, are impractical to sample – should one just move on to the next target or choose something in the locality that is accessible? Working within a Latin hypercube that spans the covariate space, selecting an alternative site is hard to do optimally. We propose flexible Latin hypercube sampling as a means of avoiding these problems. Flexible Latin hypercube sampling involves simulated annealing for optimally selecting accessible sites from a region. The sampling protocol also produces an ordered list of alternative sites close to the primary target site, should the primary target site prove inaccessible. We highlight the use of this design through a broad-scale sampling exercise in the Burdekin catchment of north Queensland, Australia. We highlight the robustness of our design through a simulation study where up to 50% of target sites may be inaccessible. [Copyright &y& Elsevier]

Abstract: Line simplification is an important task in map generalization, in traditional paper series as well as in geographic information systems and web map server services. Using the adequate method an accurate representation of the original elements should be obtained by suppression of redundant information while maintaining the shape of the original elements according to the new scale. To that effect one of the most widely used algorithms is the so-called Douglas–Peucker algorithm. It can lead to inconsistent results such as self-intersections or intersections with other elements, so the operator's supervision is necessary following the automatic treatment. In this piece of work a robust and easy-to-implement variation of the Douglas–Peucker algorithm for individual line simplification in two dimensions is presented. The robustness of the new algorithm is based on the concept of intersection of segments and it can be easily implemented in parallel. The new algorithm brings about correct results regardless of tolerance and morphology of the original line or polygon. The algorithm is coded in standard C99 and it can be compiled for serial or parallel execution via OpenMP. Both the algorithm itself and a program that implements it are distributed as free software. The validity of the solution was tested using the GSHHG geography database that can be obtained free through the Web. Results about accuracy of the output, execution speed and scalability of the parallel implementation are presented. [Copyright &y& Elsevier]

Abstract: The parameters of environmental simulation models are often inferred by minimizing differences between simulated output and observed data. Heuristic global search algorithms are a popular choice for performing minimization but many algorithms yield lackluster results when computational budgets are restricted, as is often required in practice. One way for improving performance is to limit the search domain by reducing upper and lower parameter bounds. While such range reduction is typically done prior to optimization, this study examined strategies for contracting parameter bounds during optimization. Numerical experiments evaluated a set of novel “telescoping” strategies that work in conjunction with a given optimizer to scale parameter bounds in accordance with the remaining computational budget. Various telescoping functions were considered, including a linear scaling of the bounds, and four nonlinear scaling functions that more aggressively reduce parameter bounds either early or late in the optimization. Several heuristic optimizers were integrated with the selected telescoping strategies and applied to numerous optimization test functions as well as calibration problems involving four environmental simulation models. The test suite ranged from simple 2-parameter surfaces to complex 100-parameter landscapes, facilitating robust comparisons of the selected optimizers across a variety of restrictive computational budgets. All telescoping strategies generally improved the performance of the selected optimizers, relative to baseline experiments that used no bounds reduction. Performance improvements varied but were as high as 38% for a real-coded genetic algorithm (RGA), 21% for shuffled complex evolution (SCE), 16% for simulated annealing (SA), 8% for particle swarm optimization (PSO), and 7% for dynamically dimensioned search (DDS). Inter-algorithm comparisons suggest that the SCE and DDS algorithms delivered the best overall performance. SCE appears well-suited for solving low-dimensional problems using a moderate computational budget, while DDS appears better suited for solving high-dimensional problems using a restricted computational budget. [Copyright &y& Elsevier]

Abstract: Conventional manual georegistration has been labor-intensive and time-consuming to process globally acquired high-resolution satellite imagery (HRSI) including the Korea Multi-Purpose Satellite-2 (KOMPSAT-2). While an image-to-image matching-based method can provide an automated procedure, geometric and pixel value differences such as the apparent leaning of the terrain limits an accurate georegistration. This study utilizes the projection of orthoimages into the HRSI space using external elevation data to reduce the geometric difference, and an edge matching is applied to overcome the pixel value differences. Either rigorous or replacement sensor modeling is then carried out for georegistration with robust outlier removal. An experiment for a KOMPSAT-2 strip using Digital Orthophoto Quadrangles and the Shuttle Radar Topography Mission improved the horizontal positional accuracy from 70 to only a few meters for the test data set. [Copyright &y& Elsevier]

Abstract: Even though different authors have presented procedures for camera calibration in environmental video monitoring, improvements in the robustness and accuracy of the calibration procedure are always desired and in this work the Levenberg–Marquardt method is included in the camera calibration process for environmental video monitoring images as a way to improve the robustness of the camera calibration when a low number of control points is available without using laboratory measurements. The Pinhole model and the Levenberg–Marquardt method are briefly described and a four step camera calibration procedure using them is presented. This procedure allows users to use ground control points to estimate all the Pinhole model parameters, including the lens distortion parameters and its implementation results with laboratory data are compared with the results presented by other authors. The procedure is also tested with field data obtained with cameras directed toward the beaches of the city of Cartagena, Colombia. The results show that the procedure is robust enough to be used when just a low number of control points are available, even though a large number of GCP is recommended to obtain high accuracy. [Copyright &y& Elsevier]

Abstract: Many hydrocarbon reservoirs are located near oceans which are covered by calcareous deposits. These sediments consist mainly of the remains of marine plants or animals, so calcareous soils can have a wide variety of engineering properties. Due to their local expansion and considerable differences from terrigenous soils, the evaluation of engineering behaviors of calcareous sediments has been a major concern for geotechnical engineers in recent years. Deviatoric stress is one of the most important parameters directly affecting important shearing characteristics of soils. In this study, a dataset of experimental triaxial tests was gathered from two sources. First, the data of previous experimental studies from the literature were gathered. Then, a series of triaxial tests was performed on calcareous sands of the Persian Gulf to develop the dataset. This work resulted in a large database of experimental results on the maximum deviatoric stress of different calcareous sands. To demonstrate the capabilities of evolutionary-based approaches in modeling the deviatoric stress of calcareous sands, two promising variants of genetic programming (GP), multigene genetic programming (MGP) and gene expression programming (GEP), were applied to propose new predictive models. The models’ input parameters were the physical and in-situ condition properties of soil and the output was the maximum deviatoric stress (i.e., the axial-deviator stress). The results of statistical analyses indicated the robustness of these models, and a parametric study was also conducted for further verification of the models, in which the resulting trends were consistent with the results of the experimental study. Finally, the proposed models were further simplified by applying a practical geotechnical correlation. [Copyright &y& Elsevier]

Abstract: The use of video systems for coastal monitoring purposes experienced a huge development over the last years. The main aim of this work is to present a new lightweight video monitoring system (COSMOS) that has been developed to target several key characteristics including portability, low-cost, robustness and easy installation. These characteristics were accomplished through the use of standard IP surveillance cameras and in-house developed software to correct the relative large distortion induced by the use of cameras with non-metric lens. This monitoring system has already been successfully tested in several coastal and estuarine sites with different objectives, illustrating its versatility and wide range of applicability. Research efforts are being made so that these systems can provide reliable real-time beach state indicators turning them into a key element in what concerns coastal hazard warning systems. [Copyright &y& Elsevier]

Abstract: MINERAL (MINeral ERror AnaLysis) is a MATLAB® based program that performs mineral formula recalculations and calculates the error on formula unit cations though the propagation of analytical uncertainties. The program is focused on 9 common mineral groups. Other minerals are accommodated through a generic routine in which users designate the number of cations and oxygens in the desired formula. Additional functionalities provide users with a range of mineral appropriate output options. Recalculations and uncertainty calculations include site assignments for multi-site cations (e.g. tetrahedral and octahedral Al in mafic minerals), partitioning of Fe2+ and Fe3+, and calculations of mol fractions of end members. Until now, performing full propagation of uncertainty through mineral formula recalculations was labor intensive and, for users unfamiliar with statistical notation or techniques, a significant computational challenge. The lack of precedent set by previous studies has made it accepted practice within the discipline to not provide recalculated uncertainty information. This oversight prevents analysts from assessing the quality of their data, and of their interpretations in a robust and quantitative manner. This automated toolbox renders the process fast and simple. [Copyright &y& Elsevier]

Abstract: In order to avoid the ill-conditioning problem of thin plate spline (TPS), the orthogonal least squares (OLS) method was introduced, and a modified OLS (MOLS) was developed. The MOLS of TPS (TPS-M) can not only select significant points, termed knots, from large and dense sampling data sets, but also easily compute the weights of the knots in terms of back-substitution. For interpolating large sampling points, we developed a local TPS-M, where some neighbor sampling points around the point being estimated are selected for computation. Numerical tests indicate that irrespective of sampling noise level, the average performance of TPS-M can advantage with smoothing TPS. Under the same simulation accuracy, the computational time of TPS-M decreases with the increase of the number of sampling points. The smooth fitting results on lidar-derived noise data indicate that TPS-M has an obvious smoothing effect, which is on par with smoothing TPS. The example of constructing a series of large scale DEMs, located in Shandong province, China, was employed to comparatively analyze the estimation accuracies of the two versions of TPS and the classical interpolation methods including inverse distance weighting (IDW), ordinary kriging (OK) and universal kriging with the second-order drift function (UK). Results show that regardless of sampling interval and spatial resolution, TPS-M is more accurate than the classical interpolation methods, except for the smoothing TPS at the finest sampling interval of 20m, and the two versions of kriging at the spatial resolution of 15m. In conclusion, TPS-M, which avoids the ill-conditioning problem, is considered as a robust method for DEM construction. [Copyright &y& Elsevier]

Abstract: A rock discontinuous cellular automaton (RDCA) was developed for modeling rock fracturing processes from continuous to discontinuous deformation under mechanical loading. RDCA is an integration of the following basic concepts: (1) representation of heterogeneity and strong discontinuity of rock material; (2) moving crack tracking with level set method; (3) the cellular automaton updating rule; (4) rock yield criteria and crack growth laws, etc. This model uses a local, “bottom–up” cellular automaton rule set and state input from neighboring cells to update the state of each cell in a stepped manner, avoiding the need to develop and solve large scale linear equations and the complexity therein. RDCA has the ability to simulate the non-linear and discontinuous deformation behaviors such as plastic yielding, crack initiation, propagation and coalescence etc., in the fracturing process of rocks. The theoretical background and numerical implementation of RDCA are introduced, and the associated numerical code is compiled in the C++ environment. Problems involving a central single crack, edge single crack propagation and three-point bending tests were numerically studied, and the results were compared with the analytical and experimental results to demonstrate the robustness of the method. [Copyright &y& Elsevier]

Abstract: Inversion of Rayleigh wave dispersion curves is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this paper, we proposed and tested a new Rayleigh wave dispersion curve inversion scheme called the shuffled complex evolution (SCE) approach, which is based on a synthesis of four global optimization strategies that have proved successful for global optimization: (a) combination of probabilistic and deterministic approaches; (b) the strategy of clustering; (c) systematic evolution of a complex of points spanning the space, in the direction of global improvement; and (d) competitive evolution. Incorporating these four global optimization strategies into the inverse procedure greatly enhances the performance of the SCE method because these steps not only can effectively locate the promising areas in the solution space for a global minimum but also avoid its wandering near the global minimum in the final stage of search. The proposed inverse procedure was applied to nonlinear inversion of fundamental-mode Rayleigh wave dispersion curves for near-surface shear (S)-wave velocity profiles. The calculation efficiency and stability of the inversion scheme are tested on four synthetic models and a real-world example from a waste disposal site in NE Italy. A comparative analysis with genetic algorithms (GA), marginal posterior probability density (MPPD) estimation, and simulated annealing (SA) is also made in the present study to further evaluate the performance of the proposed approach. Results from both synthetic and actual field data demonstrate that shuffled complex evolution algorithm promises to be robust, effective, and efficient for high-frequency surface wave analysis. [Copyright &y& Elsevier]

Abstract: Relationships between primary and secondary data are frequently quantified using the correlation coefficient; however, traditional means of calculating experimental correlation coefficients are known to be adversely affected by outlier data. A new method for calculating a robust correlation coefficient is proposed based on a weighted average correlation calculated from different combinations or subsets of the original data. The proposed robust correlation coefficient is shown to have a higher breakdown point than either Pearson''s or Spearman''s correlation coefficients as well as two out of three other robust correlation coefficients. The least median of squares (LMS) correlation coefficient has the highest possible breakdown point; however, it also tends to give unrealistically high or low correlation coefficients. A simulation study demonstrates the differences between the proposed robust correlation coefficient and other robust correlation coefficients. When the sample size is small, the uncertainty in the measured correlation can be very large, especially when the measured correlation is low. The uncertainty in the correlation coefficient is calculated based on the measured correlation and the number of data. This sampling distribution for the correlation coefficient requires a number of independent data; however, earth sciences data are often spatially dependent. Thus, a method for calculating an effective number of independent data using the variogram is proposed. An example is presented that applies the developed techniques to a petroleum geostatistics problem. The methodologies presented in this paper are implemented in FORTRAN code made available as part of this paper. [Copyright &y& Elsevier]

Abstract: While modern Geographic Information Systems (GIS) software is robust in handling maps and data in plan view, the software generally falls short when representing features in section view. Further complicating the issue is the fact that geologic cross sections are often drawn by connecting a series of wells together that do not fall along a single straight line. In this case, the x-axis of the cross section represents the distance along the set of individual lines connecting the series of wells, effectively “flattening out” the cross section along this path to create a view of the subsurface with which geologists often work in printed folios. Even 3D-enabled GIS cannot handle this type of cross section. A GIS data model and tools for creating and working with two-dimensional cross sections are presented. The data model and tools create a framework that can be applied using ESRI''s ArcGIS software, enabling users to create, edit, manage, and print two-dimensional cross sections from within one of the most well-known GIS software packages. The data model is a component of the arc hydro groundwater data model, which means all two-dimensional cross sections are inherently linked to other features in the hydrogeologic domain, including those represented by xyz coordinates in real world space. Thus, the creation of two-dimensional cross sections can be guided by or completely driven from standard GIS data, and geologic interpretations established on two-dimensional cross sections can be translated back to real world coordinates to create three-dimensional features such as fence diagrams, giving GIS users the capacity to characterize the subsurface environment in a variety of integrated views that was not possible before. A case study for the Sacramento Regional Model in California demonstrates the application of the methodology in support of a regional groundwater management plan. [Copyright &y& Elsevier]

Abstract: We describe a hybrid client–server technique for remote adaptive streaming and rendering of large terrains in resource-limited mobile devices. The technique has been designed to achieve an interactive rendering performance on a mobile device connected to a low-bandwidth wireless network. The rendering workload is split between the client and the server. The terrain area close to the viewer is rendered in real-time by the client. The terrain located far from the viewer is portrayed as view-dependent impostors, rendered by the server on demand. A prototype has been built and an exhaustive set of experiments covering several platforms, wireless networks and a wide range of viewer velocities has been conducted. Results show that the approach is feasible, effective and robust. [Copyright &y& Elsevier]

Abstract: This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model. [Copyright &y& Elsevier]

Abstract: For many analyses, grey scale images from X-ray tomography and other sources need to be segmented into objects and background which often is a difficult task and afflicted by an arbitrary and subjective choice of threshold values. This is especially true if the volume fraction of objects is small and the histogram becomes unimodal. Bi-level segmentation based on region growing is a promising approach to cope with the fuzzy transition zone between object and background due to the partial volume effect, but until now there is no method to properly determine the required thresholds in case of unimodality. We propose an automatic and robust technique for threshold selection based on edge detection. The method uses gradient masks which are defined as regions of interest for the determination of threshold values. Its robustness is analysed by a systematic performance test and finally demonstrated for the segmentation of pores in different soils using images from X-ray tomography. [Copyright &y& Elsevier]

Abstract: This paper presents a numerically stable solution to a point-in-polygon problem by combining the orientation method and the uniform subdivision technique. We define first a quasi-closest point that can be locally found through the uniform subdivision cells, and then we provide the criteria for determining whether a point lies inside a polygon according to the quasi-closest point. For a large number of points to be tested against the same polygon, the criteria are employed to determine the inclusion property of an empty cell as well as a test point. The experimental tests show that the new method resolves the singularity of a test point on an edge without loss of efficiency. The GIS case study also demonstrates the capability of the method to identify which region contains a test point in a map. [Copyright &y& Elsevier]

Abstract: Advanced algorithms in parallel computing can be employed for a better understanding of groundwater flow. Water flows in a very heterogeneous geological media which contains complex structures. Decomposing these structures into approximately equivalent sub-structures for load-balancing is a major challenge. This paper proposes and analyzes a new algorithm using finite element methods to simulate parallel flow fluid in such complex media. Fully parallel software is developed and numerical examples are presented to show the efficiency and robustness of the algorithm proposed. [Copyright &y& Elsevier]

Abstract: Factor analysis as a dimension reduction technique is widely used with compositional data. Using the method for raw data or for improperly transformed data will, however, lead to biased results and consequently to misleading interpretations. Although some procedures, suitable for factor analysis with compositional data, were already developed, they require pre-knowledge of variable groups, or are complicated to handle. We present an approach based on the centred logratio (clr) transformation that does not build on this pre-knowledge, but still recognizes the specific character of compositional data. In addition, by using the isometric logratio transformation it is possible to robustify factor analysis using a robust estimation of the covariance matrix. A back-transformation of the results to the clr space allows an interpretation of the results with compositional biplots. The method is demonstrated with data from the Kola project, a large ecogeochemical mapping project in northern Europe. [Copyright &y& Elsevier]