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ENGINEERING (1201 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 17)
AAPG Bulletin     Hybrid Journal   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 247)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 8)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 26)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 29)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 38)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 1)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 4)
AIChE Journal     Hybrid Journal   (Followers: 31)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 17)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 7)
Annals of Science     Hybrid Journal   (Followers: 7)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 16)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 1)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 7)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 5)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access  
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 10)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 32)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 10)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 24)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 43)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 4)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 7)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 8)
CEAS Space Journal     Hybrid Journal  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 22)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 26)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 265)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 188)
Composites Part B : Engineering     Hybrid Journal   (Followers: 278)
Composites Science and Technology     Hybrid Journal   (Followers: 182)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 14)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computers & Geosciences     Hybrid Journal   (Followers: 28)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 5)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 10)
Computing and Visualization in Science     Hybrid Journal   (Followers: 5)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 30)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 7)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 42)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
CT&F Ciencia, Tecnologia y Futuro     Open Access   (Followers: 1)
CTheory     Open Access  

        1 2 3 4 5 6 7 | Last

Journal Cover Computers & Geosciences
  [SJR: 1.268]   [H-I: 78]   [28 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0098-3004
   Published by Elsevier Homepage  [3048 journals]
  • Sensitivity of drainage morphometry based hydrological response (GIUH) of
           a river basin to the spatial resolution of DEM data
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Ramendra Sahoo, Vikrant Jain
      Drainage network pattern and its associated morphometric ratios are some of the important plan form attributes of a drainage basin. Extraction of these attributes for any basin is usually done by spatial analysis of the elevation data of that basin. These planform attributes are further used as input data for studying numerous process-response interactions inside the physical premise of the basin. One of the important uses of the morphometric ratios is its usage in the derivation of hydrologic response of a basin using GIUH concept. Hence, accuracy of the basin hydrological response to any storm event depends upon the accuracy with which, the morphometric ratios can be estimated. This in turn, is affected by the spatial resolution of the source data, i.e. the digital elevation model (DEM). We have estimated the sensitivity of the morphometric ratios and the GIUH derived hydrograph parameters, to the resolution of source data using a 30 meter and a 90 meter DEM. The analysis has been carried out for 50 drainage basins in a mountainous catchment. A simple and comprehensive algorithm has been developed for estimation of the morphometric indices from a stream network. We have calculated all the morphometric parameters and the hydrograph parameters for each of these basins extracted from two different DEMs, with different spatial resolutions. Paired t-test and Sign test were used for the comparison. Our results didn't show any statistically significant difference among any of the parameters calculated from the two source data. Along with the comparative study, a first-hand empirical analysis about the frequency distribution of the morphometric and hydrologic response parameters has also been communicated. Further, a comparison with other hydrological models suggests that plan form morphometry based GIUH model is more consistent with resolution variability in comparison to topographic based hydrological model.

      PubDate: 2017-11-16T13:32:07Z
  • Displacement prediction of Baijiabao landslide based on empirical mode
           decomposition and long short-term memory neural network in Three Gorges
           area, China
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Shiluo Xu, Ruiqing Niu
      Every year, landslides pose huge threats to thousands of people in China, especially those in the Three Gorges area. It is thus necessary to establish an early warning system to help prevent property damage and save peoples’ lives. Most of the landslide displacement prediction models that have been proposed are static models. However, landslides are dynamic systems. In this paper, the total accumulative displacement of the Baijiabao landslide is divided into trend and periodic components using empirical mode decomposition. The trend component is predicted using an S-curve estimation, and the total periodic component is predicted using a long short-term memory neural network (LSTM). LSTM is a dynamic model that can remember historical information and apply it to the current output. Six triggering factors are chosen to predict the periodic term using the Pearson cross-correlation coefficient and mutual information. These factors include the cumulative precipitation during the previous month, the cumulative precipitation during a two-month period, the reservoir level during the current month, the change in the reservoir level during the previous month, the cumulative increment of the reservoir level during the current month, and the cumulative displacement during the previous month. When using one-step-ahead prediction, LSTM yields a root mean squared error (RMSE) value of 6.112 mm, while the support vector machine for regression (SVR) and the back-propagation neural network (BP) yield values of 10.686 mm and 8.237 mm, respectively. Meanwhile, the Elman network (Elman) yields an RMSE value of 6.579 mm. In addition, when using multi-step-ahead prediction, LSTM obtains an RMSE value of 8.648 mm, while SVR, BP and the Elman network obtains RSME values of 13.418 mm, 13.014 mm, and 13.370 mm. The predicted results indicate that, to some extent, the dynamic model (LSTM) achieves results that are more accurate than those of the static models (i.e., SVR and BP). LSTM even displays better performance than the Elman network, which is also a dynamic method.

      PubDate: 2017-11-16T13:32:07Z
  • A GIS tool for two-dimensional glacier-terminus change tracking
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Jacek Andrzej Urbanski
      This paper presents a Glacier Termini Tracking (GTT) toolbox for the two-dimensional analysis of glacier-terminus position changes. The input consists of a vector layer with several termini lines relating to the same glacier at different times. The output layers allow analyses to be conducted of glacier-terminus retreats, changes in retreats over time and along the ice face, and glacier-terminus fluctuations over time. The application of three tools from the toolbox is demonstrated via the analysis of eight glacier-terminus retreats and fluctuations at the Hornsund fjord in south Svalbard. It is proposed that this toolbox may also be useful in the study of other line features that change over time, like coastlines and rivers. The toolbox has been coded in Python and runs via ArcGIS.

      PubDate: 2017-11-16T13:32:07Z
  • 2D-RBUC for efficient parallel compression of residuals
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Đorđe M. Đurđević, Igor I. Tartalja
      In this paper, we present a method for lossless compression of residuals with an efficient SIMD parallel decompression. The residuals originate from lossy or near lossless compression of height fields, which are commonly used to represent models of terrains. The algorithm is founded on the existing RBUC method for compression of non-uniform data sources. We have adapted the method to capture 2D spatial locality of height fields, and developed the data decompression algorithm for modern GPU architectures already present even in home computers. In combination with the point-level SIMD-parallel lossless/lossy high field compression method HFPaC, characterized by fast progressive decompression and seamlessly reconstructed surface, the newly proposed method trades off small efficiency degradation for a non negligible compression ratio (measured up to 91%) benefit.

      PubDate: 2017-11-16T13:32:07Z
  • Geo-social media as a proxy for hydrometeorological data for streamflow
           estimation and to improve flood monitoring
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Camilo Restrepo-Estrada, Sidgley Camargo de Andrade, Narumi Abe, Maria Clara Fava, Eduardo Mario Mendiondo, João Porto de Albuquerque
      Floods are one of the most devastating types of worldwide disasters in terms of human, economic, and social losses. If authoritative data is scarce, or unavailable for some periods, other sources of information are required to improve streamflow estimation and early flood warnings. Georeferenced social media messages are increasingly being regarded as an alternative source of information for coping with flood risks. However, existing studies have mostly concentrated on the links between geo-social media activity and flooded areas. Thus, there is still a gap in research with regard to the use of social media as a proxy for rainfall-runoff estimations and flood forecasting. To address this, we propose using a transformation function that creates a proxy variable for rainfall by analysing geo-social media messages and rainfall measurements from authoritative sources, which are later incorporated within a hydrological model for streamflow estimation. We found that the combined use of official rainfall values with the social media proxy variable as input for the Probability Distributed Model (PDM), improved streamflow simulations for flood monitoring. The combination of authoritative sources and transformed geo-social media data during flood events achieved a 71% degree of accuracy and a 29% underestimation rate in a comparison made with real streamflow measurements. This is a significant improvement on the respective values of 39% and 58%, achieved when only authoritative data were used for the modelling. This result is clear evidence of the potential use of derived geo-social media data as a proxy for environmental variables for improving flood early-warning systems.

      PubDate: 2017-11-16T13:32:07Z
  • Uncertainty management in stratigraphic well correlation and stratigraphic
           architectures: A training-based method
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Jonathan Edwards, Florent Lallier, Guillaume Caumon, Cédric Carpentier
      We discuss the sampling and the volumetric impact of stratigraphic correlation uncertainties in basins and reservoirs. From an input set of wells, we evaluate the probability for two stratigraphic units to be associated using an analog stratigraphic model. In the presence of multiple wells, this method sequentially updates a stratigraphic column defining the stratigraphic layering for each possible set of realizations. The resulting correlations are then used to create stratigraphic grids in three dimensions. We apply this method on a set of synthetic wells sampling a forward stratigraphic model built with Dionisos. To perform cross-validation of the method, we introduce a distance comparing the relative geological time of two models for each geographic position, and we compare the models in terms of volumes. Results show the ability of the method to automatically generate stratigraphic correlation scenarios, and also highlight some challenges when sampling stratigraphic uncertainties from multiple wells.
      Graphical abstract image

      PubDate: 2017-11-09T02:16:19Z
  • Method based on the Laplace equations to reconstruct the river terrain for
           two-dimensional hydrodynamic numerical modeling
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Ruixun Lai, Min Wang, Ming Yang, Chao Zhang
      The accuracy of the widely-used two-dimensional hydrodynamic numerical model depends on the quality of the river terrain model, particularly in the main channel. However, in most cases, the bathymetry of the river channel is difficult or expensive to obtain in the field, and there is a lack of available data to describe the geometry of the river channel. We introduce a method that originates from the grid generation with the elliptic equation to generate streamlines of the river channel. The streamlines are numerically solved with the Laplace equations. In the process, streamlines in the physical domain are first computed in a computational domain, and then transformed back to the physical domain. The interpolated streamlines are integrated with the surrounding topography to reconstruct the entire river terrain model. The approach was applied to a meandering reach in the Qinhe River, which is a tributary in the middle of the Yellow River, China. Cross-sectional validation and the two-dimensional shallow-water equations are used to test the performance of the river terrain generated. The results show that the approach can reconstruct the river terrain using the data from measured cross-sections. Furthermore, the created river terrain can maintain a geometrical shape consistent with the measurements, while generating a smooth main channel. Finally, several limitations and opportunities for future research are discussed.

      PubDate: 2017-11-09T02:16:19Z
  • An innovative computationally efficient hydromechanical coupling approach
           for fault reactivation in geological subsurface utilization
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): M. Adams, T. Kempka, E. Chabab, M. Ziegler
      Estimating the efficiency and sustainability of geological subsurface utilization, i.e., Carbon Capture and Storage (CCS) requires an integrated risk assessment approach, considering the occurring coupled processes, beside others, the potential reactivation of existing faults. In this context, hydraulic and mechanical parameter uncertainties as well as different injection rates have to be considered and quantified to elaborate reliable environmental impact assessments. Consequently, the required sensitivity analyses consume significant computational time due to the high number of realizations that have to be carried out. Due to the high computational costs of two-way coupled simulations in large-scale 3D multiphase fluid flow systems, these are not applicable for the purpose of uncertainty and risk assessments. Hence, an innovative semi-analytical hydromechanical coupling approach for hydraulic fault reactivation will be introduced. This approach determines the void ratio evolution in representative fault elements using one preliminary base simulation, considering one model geometry and one set of hydromechanical parameters. The void ratio development is then approximated and related to one reference pressure at the base of the fault. The parametrization of the resulting functions is then directly implemented into a multiphase fluid flow simulator to carry out the semi-analytical coupling for the simulation of hydromechanical processes. Hereby, the iterative parameter exchange between the multiphase and mechanical simulators is omitted, since the update of porosity and permeability is controlled by one reference pore pressure at the fault base. The suggested procedure is capable to reduce the computational time required by coupled hydromechanical simulations of a multitude of injection rates by a factor of up to 15.

      PubDate: 2017-11-09T02:16:19Z
  • A fast and robust TOUGH2 module to simulate geological CO2 storage in
           saline aquifers
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Babak Shabani, Javier Vilcáez
      A new TOUGH2 module to simulate geological CO2 storage (GCS) in saline aquifers is developed based on the widely employed ECO2N module of TOUGH2. The newly developed TOUGH2 module uses a new non-iterative fugacity-activity thermodynamic model to obtain the partitioning of CO2 and H2O between the aqueous and gas phases. Simple but robust thermophysical correlations are used to obtain density, viscosity, and enthalpy of the gas phase. The implementation and accuracy of the employed thermophysical correlations are verified by comparisons against the national institute of standards and technology (NIST) online thermophysical database. To assess the computation accuracy and efficiency, simulation results obtained with the new TOUGH2 module for a one-dimensional non-isothermal radial and a three-dimensional isothermal system are compared against the simulation results obtained with the ECO2N module. Treating salt mass fraction in the aqueous phase as a constant, along with the inclusion of a non-iterative fugacity-activity thermodynamic model, and simple thermophysical correlations, resulted in simulations much faster than simulations with ECO2N module, without losing numerical accuracy. Both modules yield virtually identical results. Additional field-scale simulations of CO2 injection into an actual non-isothermal and heterogeneous geological formation confirmed that the new module is much faster than the ECO2N module in simulating complex field-scale conditions. Owing to its capability to handle CO2-CH4-H2S-N2 gas mixtures and its compatibility with TOUGHREACT, this new TOUGH2 module offers the possibility of developing a fast and robust TOUGHREACT module to predict the fate of CO2 in GCS sites under biotic conditions where CO2, CH4, H2S, and N2 gases can be formed.

      PubDate: 2017-11-09T02:16:19Z
  • GIS-based rare events logistic regression for mineral prospectivity
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Yihui Xiong, Renguang Zuo
      Mineralization is a special type of singularity event, and can be considered as a rare event, because within a specific study area the number of prospective locations (1s) are considerably fewer than the number of non-prospective locations (0s). In this study, GIS-based rare events logistic regression (RELR) was used to map the mineral prospectivity in the southwestern Fujian Province, China. An odds ratio was used to measure the relative importance of the evidence variables with respect to mineralization. The results suggest that formations, granites, and skarn alterations, followed by faults and aeromagnetic anomaly are the most important indicators for the formation of Fe-related mineralization in the study area. The prediction rate and the area under the curve (AUC) values show that areas with higher probability have a strong spatial relationship with the known mineral deposits. Comparing the results with original logistic regression (OLR) demonstrates that the GIS-based RELR performs better than OLR. The prospectivity map obtained in this study benefits the search for skarn Fe-related mineralization in the study area.

      PubDate: 2017-11-09T02:16:19Z
  • A case study of forward calculations of the gravity anomaly by spectral
           method for a three-dimensional parameterised fault model
    • Abstract: Publication date: February 2018
      Source:Computers & Geosciences, Volume 111
      Author(s): Weimin Xu, Shi Chen
      Spectral methods provide many advantages for calculating gravity anomalies. In this paper, we derive a kernel function for a three-dimensional (3D) fault model in the wave number domain, and present the full Fortran source code developed for the forward computation of the gravity anomalies and related derivatives obtained from the model. The numerical error and computing speed obtained using the proposed spectral method are compared with those obtained using a 3D rectangular prism model solved in the space domain. The error obtained using the spectral method is shown to be dependent on the sequence length employed in the fast Fourier transform. The spectral method is applied to some examples of 3D fault models, and is demonstrated to be a straightforward and alternative computational approach to enhance computational speed and simplify the procedures for solving many gravitational potential forward problems involving complicated geological models. The proposed method can generate a great number of feasible geophysical interpretations based on a 3D model with only a few variables, and can thereby improve the efficiency of inversion.

      PubDate: 2017-11-09T02:16:19Z
  • Hyper-resolution monitoring of urban flooding with social media and
           crowdsourcing data
    • Abstract: Publication date: Available online 8 November 2017
      Source:Computers & Geosciences
      Author(s): Ruo-Qian Wang, Huina Mao, Yuan Wang, Chris Rae, Wesley Shaw
      Hyper-resolution datasets for urban flooding are rare. This problem prevents detailed flooding risk analysis, urban flooding control, and the validation of hyper-resolution numerical models. We employed social media and crowdsourcing data to address this issue. Natural Language Processing and Computer Vision techniques are applied to the data collected from Twitter and MyCoast (a crowdsourcing app). We found these big data based flood monitoring approaches can complement the existing means of flood data collection. The extracted information is validated against precipitation data and road closure reports to examine the data quality. The two data collection approaches are compared and the two data mining methods are discussed. A series of suggestions is given to improve the data collection strategy.

      PubDate: 2017-11-09T02:16:19Z
  • (Non-) homomorphic approaches to denoise intensity SAR images with
           non-local means and stochastic distances
    • Abstract: Publication date: Available online 6 November 2017
      Source:Computers & Geosciences
      Author(s): Pedro A.A. Penna, Nelson D.A. Mascarenhas
      The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G 0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G 0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

      PubDate: 2017-11-09T02:16:19Z
  • Coupled X-ray computed tomography and grey level co-occurrence matrices as
           a method for quantification of mineralogy and texture in 3D
    • Abstract: Publication date: Available online 6 November 2017
      Source:Computers & Geosciences
      Author(s): M.A. Jardine, J.A. Miller, M. Becker
      Texture is one of the most basic descriptors used in the geological sciences. The value derived from textural characterisation extends into engineering applications associated with mining, mineral processing and metal extraction where quantitative textural information is required for models predicting the response of the ore through a particular process. This study extends the well-known 2D grey level co-occurrence matrices methodology into 3D as a method for image analysis of 3D x-ray computed tomography grey scale volumes of drill core. Subsequent interrogation of the information embedded within the grey level occurrence matrices (GLCM) indicates they are sensitive to changes in mineralogy and texture of samples derived from a magmatic nickel sulfide ore. The position of the peaks in the GLCM is an indication of the relative density (specific gravity, SG) of the minerals and when interpreted using a working knowledge of the mineralogy of the ore presented a means to determine the relative abundance of the sulfide minerals (SG > 4), dense silicate minerals (SG > 3), and lighter silicate minerals (SG < 3). The spread of the peaks in the GLCM away from the diagonal is an indication of the degree of grain boundary interaction with wide peaks representing fine grain sizes and narrow peaks representing coarse grain sizes. The method lends itself to application as part of a generic methodology for routine use on large XCT volumes providing quantitative, timely, meaningful and automated information on mineralogy and texture in 3D.
      Graphical abstract image

      PubDate: 2017-11-09T02:16:19Z
  • The introspective may achieve more: Enhancing existing Geoscientific
           models with native-language emulated structural reflection
    • Abstract: Publication date: January 2018
      Source:Computers & Geosciences, Volume 110
      Author(s): Xinye Ji, Chaopeng Shen
      Geoscientific models manage myriad and increasingly complex data structures as trans-disciplinary models are integrated. They often incur significant redundancy with cross-cutting tasks. Reflection, the ability of a program to inspect and modify its structure and behavior at runtime, is known as a powerful tool to improve code reusability, abstraction, and separation of concerns. Reflection is rarely adopted in high-performance Geoscientific models, especially with Fortran, where it was previously deemed implausible. Practical constraints of language and legacy often limit us to feather-weight, native-language solutions. We demonstrate the usefulness of a structural-reflection-emulating, dynamically-linked metaObjects, gd. We show real-world examples including data structure self-assembly, effortless input/output (IO) and upgrade to parallel I/O, recursive actions and batch operations. We share gd and a derived module that reproduces MATLAB-like structure in Fortran and C++. We suggest that both a gd representation and a Fortran-native representation are maintained to access the data, each for separate purposes. Embracing emulated reflection allows generically-written codes that are highly re-usable across projects.

      PubDate: 2017-11-02T08:38:47Z
  • GSpecDisp: A matlab GUI package for phase-velocity dispersion measurements
           from ambient-noise correlations
    • Abstract: Publication date: January 2018
      Source:Computers & Geosciences, Volume 110
      Author(s): Hamzeh Sadeghisorkhani, Ólafur Gudmundsson, Ari Tryggvason
      We present a graphical user interface (GUI) package to facilitate phase-velocity dispersion measurements of surface waves in noise-correlation traces. The package, called GSpecDisp, provides an interactive environment for the measurements and presentation of the results. The selection of a dispersion curve can be done automatically or manually within the package. The data are time-domain cross-correlations in SAC format, but GSpecDisp measures phase velocity in the spectral domain. Two types of phase-velocity dispersion measurements can be carried out with GSpecDisp; (1) average velocity of a region, and (2) single-pair phase velocity. Both measurements are done by matching the real part of the cross-correlation spectrum with the appropriate Bessel function. Advantages of these two types of measurements are that no prior knowledge about surface-wave dispersion in the region is needed, and that phase velocity can be measured up to that period for which the inter-station distance corresponds to one wavelength. GSpecDisp can measure the phase velocity of Rayleigh and Love waves from all possible components of the noise correlation tensor. First, we briefly present the theory behind the methods that are used, and then describe different modules of the package. Finally, we validate the developed algorithms by applying them to synthetic and real data, and by comparison with other methods. The source code of GSpecDisp can be downloaded from:

      PubDate: 2017-11-02T08:38:47Z
  • Intelligent inversion method for pre-stack seismic big data based on
    • Abstract: Publication date: January 2018
      Source:Computers & Geosciences, Volume 110
      Author(s): Xuesong Yan, Zhixin Zhu, Qinghua Wu
      Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

      PubDate: 2017-11-02T08:38:47Z
  • A density-based clustering algorithm for earthquake zoning
    • Abstract: Publication date: January 2018
      Source:Computers & Geosciences, Volume 110
      Author(s): Sanja Scitovski
      A possibility of applying the density-based clustering algorithm Rough-DBSCAN for earthquake zoning is considered in the paper. By using density-based clustering for earthquake zoning it is possible to recognize nonconvex shapes, what gives much more realistic results. Special attention is thereby paid to the problem of determining the corresponding value of the parameter ɛ in the algorithm. The size of the parameter ɛ significantly influences the recognizing number and configuration of earthquake zones. A method for selecting the parameter ɛ in the case of big data is also proposed. The method is applied to the problem of earthquake data zoning in a wider area of the Republic of Croatia.

      PubDate: 2017-11-02T08:38:47Z
  • pySCu: A new python code for analyzing remagnetizations directions by
           means of small circle utilities
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Pablo Calvín, Juan J. Villalaín, Antonio M. Casas-Sainz, Lisa Tauxe, Sara Torres-López
      The Small Circle (SC) methods are founded upon two main starting hypotheses: (i) the analyzed sites were remagnetized contemporarily, acquiring the same paleomagnetic direction. (ii) The deviation of the acquired paleomagnetic signal from its original direction is only due to tilting around the bedding strike and therefore the remagnetization direction must be located on a small circle (SC) whose axis is the strike of bedding and contains the in situ paleomagnetic direction. Therefore, if we analyze several sites (with different bedding strikes) their SCs will intersect in the remagnetization direction. The SC methods have two applications: (1) the Small Circle Intersection (SCI) method is capable of providing adequate approximations to the expected paleomagnetic direction when dealing with synfolding remagnetizations. By comparing the SCI direction with that predicted from an apparent polar wander path, the (re)magnetization can be dated. (2) Once the remagnetization direction is known, the attitude of the beds (at each site) can be restored to the moment of the acquisition of the remagnetization, showing a palinspastic reconstructuion of the structure. Some caveats are necessary under more complex tectonic scenarios, in which SC-based methods can lead to erroneous interpretations. However, the graphical output of the methods tries to avoid ‘black-box’ effects and can minimize misleading interpretations or even help, for example, to identify local or regional vertical axis rotations. In any case, the methods must be used with caution and always considering the knowledge of the tectonic frame. In this paper, some utilities for SCs analysis are automatized by means of a new Python code and a new technique for defining the uncertainty of the solution is proposed. With pySCu the SCs methods can be easily and quickly applied, obtaining firstly a set of text files containing all calculated information and subsequently generating a graphical output on the fly.
      Graphical abstract image

      PubDate: 2017-10-26T08:29:36Z
  • Phase Composition Maps integrate mineral compositions with rock textures
           from the micro-meter to the thin section scale
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Kyle V. Willis, LeeAnn Srogi, Tim Lutz, Frederick C. Monson, Meagen Pollock
      Textures and compositions are critical information for interpreting rock formation. Existing methods to integrate both types of information favor high-resolution images of mineral compositions over small areas or low-resolution images of larger areas for phase identification. The method in this paper produces images of individual phases in which textural and compositional details are resolved over three orders of magnitude, from tens of micrometers to tens of millimeters. To construct these images, called Phase Composition Maps (PCMs), we make use of the resolution in backscattered electron (BSE) images and calibrate the gray scale values with mineral analyses by energy-dispersive X-ray spectrometry (EDS). The resulting images show the area of a standard thin section (roughly 40 mm × 20 mm) with spatial resolution as good as 3.5 μm/pixel, or more than 81 000 pixels/mm2, comparable to the resolution of X-ray element maps produced by wavelength-dispersive spectrometry (WDS). Procedures to create PCMs for mafic igneous rocks with multivariate linear regression models for minerals with solid solution (olivine, plagioclase feldspar, and pyroxenes) are presented and are applicable to other rock types. PCMs are processed using threshold functions based on the regression models to image specific composition ranges of minerals. PCMs are constructed using widely-available instrumentation: a scanning-electron microscope (SEM) with BSE and EDS X-ray detectors and standard image processing software such as ImageJ and Adobe Photoshop. Three brief applications illustrate the use of PCMs as petrologic tools: to reveal mineral composition patterns at multiple scales; to generate crystal size distributions for intracrystalline compositional zones and compare growth over time; and to image spatial distributions of minerals at different stages of magma crystallization by integrating textures and compositions with thermodynamic modeling.

      PubDate: 2017-10-26T08:29:36Z
  • A density based algorithm to detect cavities and holes from planar points
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Jie Zhu, Yizhong Sun, Yueyong Pang
      Delaunay-based shape reconstruction algorithms are widely used in approximating the shape from planar points. However, these algorithms cannot ensure the optimality of varied reconstructed cavity boundaries and hole boundaries. This inadequate reconstruction can be primarily attributed to the lack of efficient mathematic formulation for the two structures (hole and cavity). In this paper, we develop an efficient algorithm for generating cavities and holes from planar points. The algorithm yields the final boundary based on an iterative removal of the Delaunay triangulation. Our algorithm is mainly divided into two steps, namely, rough and refined shape reconstructions. The rough shape reconstruction performed by the algorithm is controlled by a relative parameter. Based on the rough result, the refined shape reconstruction mainly aims to detect holes and pure cavities. Cavity and hole are conceptualized as a structure with a low-density region surrounded by the high-density region. With this structure, cavity and hole are characterized by a mathematic formulation called as compactness of point formed by the length variation of the edges incident to point in Delaunay triangulation. The boundaries of cavity and hole are then found by locating a shape gradient change in compactness of point set. The experimental comparison with other shape reconstruction approaches shows that the proposed algorithm is able to accurately yield the boundaries of cavity and hole with varying point set densities and distributions.

      PubDate: 2017-10-26T08:29:36Z
  • Finite-element time-domain modeling of electromagnetic data in general
           dispersive medium using adaptive Padé series
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Hongzhu Cai, Xiangyun Hu, Bin Xiong, Michael S. Zhdanov
      The induced polarization (IP) method has been widely used in geophysical exploration to identify the chargeable targets such as mineral deposits. The inversion of the IP data requires modeling the IP response of 3D dispersive conductive structures. We have developed an edge-based finite-element time-domain (FETD) modeling method to simulate the electromagnetic (EM) fields in 3D dispersive medium. We solve the vector Helmholtz equation for total electric field using the edge-based finite-element method with an unstructured tetrahedral mesh. We adopt the backward propagation Euler method, which is unconditionally stable, with semi-adaptive time stepping for the time domain discretization. We use the direct solver based on a sparse LU decomposition to solve the system of equations. We consider the Cole-Cole model in order to take into account the frequency-dependent conductivity dispersion. The Cole-Cole conductivity model in frequency domain is expanded using a truncated Padé series with adaptive selection of the center frequency of the series for early and late time. This approach can significantly increase the accuracy of FETD modeling.

      PubDate: 2017-10-26T08:29:36Z
  • Web processing service for climate impact and extreme weather event
           analyses. Flyingpigeon (Version 1.0)
    • Abstract: Publication date: January 2018
      Source:Computers & Geosciences, Volume 110
      Author(s): Nils Hempelmann, Carsten Ehbrecht, Carmen Alvarez-Castro, Patrick Brockmann, Wolfgang Falk, Jörg Hoffmann, Stephan Kindermann, Ben Koziol, Cathy Nangini, Sabine Radanovics, Robert Vautard, Pascal Yiou
      Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files “at home” with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named ‘flyingpigeon’ that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC), to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues, illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets.

      PubDate: 2017-10-18T13:36:41Z
  • Local PEBI grid generation method for reverse faults
    • Abstract: Publication date: Available online 28 September 2017
      Source:Computers & Geosciences
      Author(s): Xianhai Meng, Zhongxiang Duan, Qin Yang, Xing Liang
      The 2.5D PEBI (PErpendicular BIsector) grid, which is the projection or extrusion of the 2D PEBI gird, has advantages on practical reservoir modeling. However, to appropriately handle the geological features, especially the reverse faults in reservoir, remains a difficult problem. To address this issue, we propose a local PEBI grid generation method in this paper. By constructing the Voronoi cell of a seed based on the search of its neighboring seeds in a background grid, our method is demonstrated to be efficient and adaptable to reverse fault constraints. In addition, the vertical and horizontal well constraints are also tackled and the cell quality is improved through the Centroidal Voronoi Tessellations (CVT) principle. The results demonstrated that our method enables the formation of high-quality grids and guarantees the conformity to the geological features in reservoirs.

      PubDate: 2017-10-04T08:24:41Z
  • In situ visualization and data analysis for turbidity currents simulation
    • Abstract: Publication date: Available online 28 September 2017
      Source:Computers & Geosciences
      Author(s): Jose J. Camata, Vítor Silva, Patrick Valduriez, Marta Mattoso, Alvaro L.G.A. Coutinho
      Turbidity currents are underflows responsible for sediment deposits that generate geological formations of interest for the oil and gas industry. LibMesh-sedimentation is an application built upon the libMesh library to simulate turbidity currents. In this work, we present the integration of libMesh-sedimentation with in situ visualization and in transit data analysis tools. DfAnalyzer is a solution based on provenance data to extract and relate strategic simulation data in transit from multiple data for online queries. We integrate libMesh-sedimentation and ParaView Catalyst to perform in situ data analysis and visualization. We present a parallel performance analysis for two turbidity currents simulations showing that the overhead for both in situ visualization and in transit data analysis is negligible. We show that our tools enable monitoring the sediments appearance at runtime and steer the simulation based on the solver convergence and visual information on the sediment deposits, thus enhancing the analytical power of turbidity currents simulations.

      PubDate: 2017-10-04T08:24:41Z
  • OpenMP parallelization of a gridded SWAT (SWATG)
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Ying Zhang, Jinliang Hou, Yongpan Cao, Juan Gu, Chunlin Huang
      Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

      PubDate: 2017-09-26T03:50:47Z
  • Joint simulation of stationary grade and non-stationary rock type for
           quantifying geological uncertainty in a copper deposit
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Mohammad Maleki, Xavier Emery
      In mineral resources evaluation, the joint simulation of a quantitative variable, such as a metal grade, and a categorical variable, such as a rock type, is challenging when one wants to reproduce spatial trends of the rock type domains, a feature that makes a stationarity assumption questionable. To address this problem, this work presents methodological and practical proposals for jointly simulating a grade and a rock type, when the former is represented by the transform of a stationary Gaussian random field and the latter is obtained by truncating an intrinsic random field of order k with Gaussian generalized increments. The proposals concern both the inference of the model parameters and the construction of realizations conditioned to existing data. The main difficulty is the identification of the spatial correlation structure, for which a semi-automated algorithm is designed, based on a least squares fitting of the data-to-data indicator covariances and grade-indicator cross-covariances. The proposed models and algorithms are applied to jointly simulate the copper grade and the rock type in a Chilean porphyry copper deposit. The results show their ability to reproduce the gradual transitions of the grade when crossing a rock type boundary, as well as the spatial zonation of the rock type.

      PubDate: 2017-09-26T03:50:47Z
  • A path-level exact parallelization strategy for sequential simulation
    • Abstract: Publication date: Available online 23 September 2017
      Source:Computers & Geosciences
      Author(s): Oscar F. Peredo, Daniel Baeza, Julián M. Ortiz, José R. Herrero
      Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non-conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB: SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.

      PubDate: 2017-09-26T03:50:47Z
  • Reynolds number and settling velocity influence for finite-release
           particle-laden gravity currents in a basin
    • Abstract: Publication date: Available online 22 September 2017
      Source:Computers & Geosciences
      Author(s): E.P. Francisco, L.F.R. Espath, S. Laizet, J.H. Silvestrini
      Three-dimensional highly resolved Direct Numerical Simulations (DNS) of particle-laden gravity currents are presented for the lock-exchange problem in an original basin configuration, similar to delta formation in lakes. For this numerical study, we focus on gravity currents over a flat bed for which density differences are small enough for the Boussinesq approximation to be valid. The concentration of particles is described in an Eulerian fashion by using a transport equation combined with the incompressible Navier-Stokes equations, with the possibility of particles deposition but no erosion nor re-suspension. The focus of this study is on the influence of the Reynolds number and settling velocity on the development of the current which can freely evolve in the streamwise and spanwise direction. It is shown that the settling velocity has a strong influence on the spatial extent of the current, the sedimentation rate, the suspended mass and the shape of the lobe-and-cleft structures while the Reynolds number is mainly affecting the size and number of vortical structures at the front of the current, and the energy budget.

      PubDate: 2017-09-26T03:50:47Z
  • A novel orthoimage mosaic method using the weighted A* algorithm for UAV
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Maoteng Zheng, Shunping Zhou, Xiaodong Xiong, Junfeng Zhu
      A weighted A* algorithm is proposed to select optimal seam-lines in orthoimage mosaic for UAV (Unmanned Aircraft Vehicle) imagery. The whole workflow includes four steps: the initial seam-line network is firstly generated by standard Voronoi Diagram algorithm; an edge diagram is then detected based on DSM (Digital Surface Model) data; the vertices (conjunction nodes) of initial network are relocated since some of them are on the high objects (buildings, trees and other artificial structures); and, the initial seam-lines are finally refined using the weighted A* algorithm based on the edge diagram and the relocated vertices. The method was tested with two real UAV datasets. Preliminary results show that the proposed method produces acceptable mosaic images in both the urban and mountainous areas, and is better than the result of the state-of-the-art methods on the datasets.

      PubDate: 2017-09-20T06:44:46Z
  • New spatial upscaling methods for multi-point measurements: From normal to
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Feng Liu, Xin Li
      Careful attention must be given to determining whether the geophysical variables of interest are normally distributed, since the assumption of a normal distribution may not accurately reflect the probability distribution of some variables. As a generalization of the normal distribution, the p-normal distribution and its corresponding maximum likelihood estimation (the least power estimation, LPE) were introduced in upscaling methods for multi-point measurements. Six methods, including three normal-based methods, i.e., arithmetic average, least square estimation, block kriging, and three p-normal-based methods, i.e., LPE, geostatistics LPE and inverse distance weighted LPE are compared in two types of experiments: a synthetic experiment to evaluate the performance of the upscaling methods in terms of accuracy, stability and robustness, and a real-world experiment to produce real-world upscaling estimates using soil moisture data obtained from multi-scale observations. The results show that the p-normal-based methods produced lower mean absolute errors and outperformed the other techniques due to their universality and robustness. We conclude that introducing appropriate statistical parameters into an upscaling strategy can substantially improve the estimation, especially if the raw measurements are disorganized; however, further investigation is required to determine which parameter is the most effective among variance, spatial correlation information and parameter p.

      PubDate: 2017-09-20T06:44:46Z
  • Geo3DML: A standard-based exchange format for 3D geological models
    • Abstract: Publication date: Available online 18 September 2017
      Source:Computers & Geosciences
      Author(s): Zhangang Wang, Honggang Qu, Zixing Wu, Xianghong Wang
      A geological model (geomodel) in three-dimensional (3D) space is a digital representation of the Earth's subsurface, recognized by geologists and stored in resultant geological data (geodata). The increasing demand for data management and interoperable applications of geomodelscan be addressed by developing standard-based exchange formats for the representation of not only a single geological object, but also holistic geomodels. However, current standards such as GeoSciML cannot incorporate all the geomodel-related information. This paper presents Geo3DML for the exchange of 3D geomodels based on the existing Open Geospatial Consortium (OGC) standards. Geo3DML is based on a unified and formal representation of structural models, attribute models and hierarchical structures of interpreted resultant geodata in different dimensional views, including drills, cross-sections/geomaps and 3D models, which is compatible with the conceptual model of GeoSciML. Geo3DML aims to encode all geomodel-related information integrally in one framework, including the semantic and geometric information of geoobjects and their relationships, as well as visual information. At present, Geo3DML and some supporting tools have been released as a data-exchange standard by the China Geological Survey (CGS).

      PubDate: 2017-09-20T06:44:46Z
  • Fast automated airborne electromagnetic data interpretation using
           parallelized particle swarm optimization
    • Abstract: Publication date: Available online 17 September 2017
      Source:Computers & Geosciences
      Author(s): Jacques K. Desmarais, Raymond J. Spiteri
      A parallelized implementation of the particle swarm optimization algorithm is developed. We use the optimization procedure to speed up a previously published algorithm for airborne electromagnetic data interpretation. This algorithm is the only parametrized automated procedure for extracting the three-dimensionally varying geometrical parameters of conductors embedded in a resistive environment, such as igneous and metamorphic terranes. When compared to the original algorithm, the new optimization procedure is faster by two orders of magnitude (factor of 100). Synthetic model tests show that for the chosen system architecture and objective function, the particle swarm optimization approach depends very weakly on the rate of communication of the processors. Optimal wall-clock times are obtained using three processors. The increased performance means that the algorithm can now easily be used for fast routine interpretation of airborne electromagnetic surveys consisting of several anomalies, as is displayed by a test on MEGATEM field data collected at the Chibougamau site, Québec.

      PubDate: 2017-09-20T06:44:46Z
  • TReacLab: An object-oriented implementation of non-intrusive splitting
           methods to couple independent transport and geochemical software
    • Abstract: Publication date: Available online 13 September 2017
      Source:Computers & Geosciences
      Author(s): Daniel Jara, Jean-Raynald de Dreuzy, Benoit Cochepin
      Reactive transport modeling contributes to understand geophysical and geochemical processes in subsurface environments. Operator splitting methods have been proposed as non-intrusive coupling techniques that optimize the use of existing chemistry and transport codes. In this spirit, we propose a coupler relying on external geochemical and transport codes with appropriate operator segmentation that enables possible developments of additional splitting methods. We provide an object-oriented implementation in TReacLab developed in the MATLAB environment in a free open source frame with an accessible repository. TReacLab contains classical coupling methods, template interfaces and calling functions for two classical transport and reactive software (PHREEQC and COMSOL). It is tested on four classical benchmarks with homogeneous and heterogeneous reactions at equilibrium or kinetically-controlled. We show that full decoupling to the implementation level has a cost in terms of accuracy compared to more integrated and optimized codes. Use of non-intrusive implementations like TReacLab are still justified for coupling independent transport and chemical software at a minimal development effort but should be systematically and carefully assessed.

      PubDate: 2017-09-13T16:37:24Z
  • A continuous scale-space method for the automated placement of spot
           heights on maps
    • Abstract: Publication date: Available online 9 September 2017
      Source:Computers & Geosciences
      Author(s): Luigi Rocca, Bernhard Jenny, Enrico Puppo
      Spot heights and soundings explicitly indicate terrain elevation on cartographic maps. Cartographers have developed design principles for the manual selection, placement, labeling, and generalization of spot height locations, but these processes are work-intensive and expensive. Finding an algorithmic criterion that matches the cartographers’ judgment in ranking the significance of features on a terrain is a difficult endeavor. This article proposes a method for the automated selection of spot heights locations representing natural features such as peaks, saddles and depressions. A lifespan of critical points in a continuous scale-space model is employed as the main measure of the importance of features, and an algorithm and a data structure for its computation are described. We also introduce a method for the comparison of algorithmically computed spot height locations with manually produced reference compilations. The new method is compared with two known techniques from the literature. Results show spot height locations that are closer to reference spot heights produced manually by swisstopo cartographers, compared to previous techniques. The introduced method can be applied to elevation models for the creation of topographic and bathymetric maps. It also ranks the importance of extracted spot height locations, which allows for a variation in the size of symbols and labels according to the significance of represented features. The importance ranking could also be useful for adjusting spot height density of zoomable maps in real time.

      PubDate: 2017-09-13T16:37:24Z
  • Big geo data surface approximation using radial basis functions: A
           comparative study
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Zuzana Majdisova, Vaclav Skala
      Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in n–dimensional space. It is a non-separable approximation, as it is based on the distance between two points. This method leads to the solution of an overdetermined linear system of equations. In this paper the RBF approximation methods are briefly described, a new approach to the RBF approximation of big datasets is presented, and a comparison for different Compactly Supported RBFs (CS-RBFs) is made with respect to the accuracy of the computation. The proposed approach uses symmetry of a matrix, partitioning the matrix into blocks and data structures for storage of the sparse matrix. The experiments are performed for synthetic and real datasets.

      PubDate: 2017-09-02T08:49:18Z
  • Classification of radiolarian images with hand-crafted and deep features
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Ali Seydi Keçeli, Aydın Kaya, Seda Uzunçimen Keçeli
      Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

      PubDate: 2017-09-02T08:49:18Z
  • Stochastic seismic inversion based on an improved local gradual
           deformation method
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Xiuwei Yang, Peimin Zhu
      A new stochastic seismic inversion method based on the local gradual deformation method is proposed, which can incorporate seismic data, well data, geology and their spatial correlations into the inversion process. Geological information, such as sedimentary facies and structures, could provide significant a priori information to constrain an inversion and arrive at reasonable solutions. The local a priori conditional cumulative distributions at each node of model to be inverted are first established by indicator cokriging, which integrates well data as hard data and geological information as soft data. Probability field simulation is used to simulate different realizations consistent with the spatial correlations and local conditional cumulative distributions. The corresponding probability field is generated by the fast Fourier transform moving average method. Then, optimization is performed to match the seismic data via an improved local gradual deformation method. Two improved strategies are proposed to be suitable for seismic inversion. The first strategy is that we select and update local areas of bad fitting between synthetic seismic data and real seismic data. The second one is that we divide each seismic trace into several parts and obtain the optimal parameters for each part individually. The applications to a synthetic example and a real case study demonstrate that our approach can effectively find fine-scale acoustic impedance models and provide uncertainty estimations.

      PubDate: 2017-09-02T08:49:18Z
  • Animated analysis of geoscientific datasets: An interactive graphical
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Peter Morse, Anya Reading, Christopher Lueg
      Geoscientists are required to analyze and draw conclusions from increasingly large volumes of data. There is a need to recognise and characterise features and changing patterns of Earth observables within such large datasets. It is also necessary to identify significant subsets of the data for more detailed analysis. We present an innovative, interactive software tool and workflow to visualise, characterise, sample and tag large geoscientific datasets from both local and cloud-based repositories. It uses an animated interface and human-computer interaction to utilise the capacity of human expert observers to identify features via enhanced visual analytics. ‘Tagger’ enables users to analyze datasets that are too large in volume to be drawn legibly on a reasonable number of single static plots. Users interact with the moving graphical display, tagging data ranges of interest for subsequent attention. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling and is coded in the Quartz Composer visual programing language (VPL) on Mac OSX. It makes use of interoperable data formats, and cloud-based (or local) data storage and compute. In a case study, Tagger was used to characterise a decade (2000–2009) of data recorded by the Cape Sorell Waverider Buoy, located approximately 10 km off the west coast of Tasmania, Australia. These data serve as a proxy for the understanding of Southern Ocean storminess, which has both local and global implications. This example shows use of the tool to identify and characterise 4 different types of storm and non-storm events during this time. Events characterised in this way are compared with conventional analysis, noting advantages and limitations of data analysis using animation and human interaction. Tagger provides a new ability to make use of humans as feature detectors in computer-based analysis of large-volume geosciences and other data.

      PubDate: 2017-09-02T08:49:18Z
  • A 3D joint interpretation of magnetotelluric and seismic tomographic
           models: The case of the volcanic island of Tenerife
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Araceli García-Yeguas, Juanjo Ledo, Perla Piña-Varas, Janire Prudencio, Pilar Queralt, Alex Marcuello, Jesús M. Ibañez, Beatriz Benjumea, Alberto Sánchez-Alzola, Nemesio Pérez
      In this work we have done a 3D joint interpretation of magnetotelluric and seismic tomography models. Previously we have described different techniques to infer the inner structure of the Earth. We have focused on volcanic regions, specifically on Tenerife Island volcano (Canary Islands, Spain). In this area, magnetotelluric and seismic tomography studies have been done separately. The novelty of the present work is the combination of both techniques in Tenerife Island. For this aim we have applied Fuzzy Clusters Method at different depths obtaining several clusters or classes. From the results, a geothermal system has been inferred below Teide volcano, in the center of Tenerife Island. An edifice hydrothermally altered and full of fluids is situated below Teide, ending at 600 m below sea level. From this depth the resistivity and VP values increase downwards. We also observe a clay cap structure, a typical feature in geothermal systems related with low resistivity and low VP values.

      PubDate: 2017-09-02T08:49:18Z
  • pyGIMLi: An open-source library for modelling and inversion in geophysics
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Carsten Rücker, Thomas Günther, Florian M. Wagner
      Many tasks in applied geosciences cannot be solved by single measurements, but require the integration of geophysical, geotechnical and hydrological methods. Numerical simulation techniques are essential both for planning and interpretation, as well as for the process understanding of modern geophysical methods. These trends encourage open, simple, and modern software architectures aiming at a uniform interface for interdisciplinary and flexible modelling and inversion approaches. We present pyGIMLi (Python Library for Inversion and Modelling in Geophysics), an open-source framework that provides tools for modelling and inversion of various geophysical but also hydrological methods. The modelling component supplies discretization management and the numerical basis for finite-element and finite-volume solvers in 1D, 2D and 3D on arbitrarily structured meshes. The generalized inversion framework solves the minimization problem with a Gauss-Newton algorithm for any physical forward operator and provides opportunities for uncertainty and resolution analyses. More general requirements, such as flexible regularization strategies, time-lapse processing and different sorts of coupling individual methods are provided independently of the actual methods used. The usage of pyGIMLi is first demonstrated by solving the steady-state heat equation, followed by a demonstration of more complex capabilities for the combination of different geophysical data sets. A fully coupled hydrogeophysical inversion of electrical resistivity tomography (ERT) data of a simulated tracer experiment is presented that allows to directly reconstruct the underlying hydraulic conductivity distribution of the aquifer. Another example demonstrates the improvement of jointly inverting ERT and ultrasonic data with respect to saturation by a new approach that incorporates petrophysical relations in the inversion. Potential applications of the presented framework are manifold and include time-lapse, constrained, joint, and coupled inversions of various geophysical and hydrological data sets.

      PubDate: 2017-09-02T08:49:18Z
  • A constrained Delaunay discretization method for adaptively meshing highly
           discontinuous geological media
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Yang Wang, Guowei Ma, Feng Ren, Tuo Li
      A constrained Delaunay discretization method is developed to generate high-quality doubly adaptive meshes of highly discontinuous geological media. Complex features such as three-dimensional discrete fracture networks (DFNs), tunnels, shafts, slopes, boreholes, water curtains, and drainage systems are taken into account in the mesh generation. The constrained Delaunay triangulation method is used to create adaptive triangular elements on planar fractures. Persson's algorithm (Persson, 2005), based on an analogy between triangular elements and spring networks, is enriched to automatically discretize a planar fracture into mesh points with varying density and smooth-quality gradient. The triangulated planar fractures are treated as planar straight-line graphs (PSLGs) to construct piecewise-linear complex (PLC) for constrained Delaunay tetrahedralization. This guarantees the doubly adaptive characteristic of the resulted mesh: the mesh is adaptive not only along fractures but also in space. The quality of elements is compared with the results from an existing method. It is verified that the present method can generate smoother elements and a better distribution of element aspect ratios. Two numerical simulations are implemented to demonstrate that the present method can be applied to various simulations of complex geological media that contain a large number of discontinuities.

      PubDate: 2017-09-02T08:49:18Z
  • Automatic extraction of blocks from 3D point clouds of fractured rock
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Na Chen, John Kemeny, Qinghui Jiang, Zhiwen Pan
      This paper presents a new method for extracting blocks and calculating block size automatically from rock surface 3D point clouds. Block size is an important rock mass characteristic and forms the basis for several rock mass classification schemes. The proposed method consists of four steps: 1) the automatic extraction of discontinuities using an improved Ransac Shape Detection method, 2) the calculation of discontinuity intersections based on plane geometry, 3) the extraction of block candidates based on three discontinuities intersecting one another to form corners, and 4) the identification of “true” blocks using an improved Floodfill algorithm. The calculated block sizes were compared with manual measurements in two case studies, one with fabricated cardboard blocks and the other from an actual rock mass outcrop. The results demonstrate that the proposed method is accurate and overcomes the inaccuracies, safety hazards, and biases of traditional techniques.

      PubDate: 2017-09-02T08:49:18Z
  • A Variable Resolution Right TIN Approach for Gridded Oceanographic Data
    • Abstract: Publication date: Available online 31 July 2017
      Source:Computers & Geosciences
      Author(s): David Marks, Paul Elmore, Cheryl Ann Blain, Brian Bourgeois, Frederick Petry, Vicki Ferrini
      Many oceanographic applications require multi resolution representation of gridded data such as for bathymetric data. Although triangular irregular networks (TINs) allow for variable resolution, they do not provide a gridded structure. Right TINs (RTINs) are compatible with a gridded structure. We explored the use of two approaches for RTINs termed top-down and bottom-up implementations. We illustrate why the latter is most appropriate for gridded data and describe for this technique how the data can be thinned. While both the top-down and bottom-up approaches accurately preserve the surface morphology of any given region, the top-down method of vertex placement can fail to match the actual vertex locations of the underlying grid in many instances, resulting in obscured topology / bathymetry. Finally we describe the use of the bottom-up approach and data thinning in two applications. The first is to provide thinned, variable resolution bathymetry data for tests of storm surge and inundation modeling, in particular hurricane Katrina. Secondly we consider the use of the approach for an application to an oceanographic data grid of 3-D ocean temperature.

      PubDate: 2017-08-03T07:30:56Z
  • TouchTerrain: A simple web-tool for creating 3D-printable topographic
    • Abstract: Publication date: Available online 25 July 2017
      Source:Computers & Geosciences
      Author(s): Franciszek J. Hasiuk, Chris Harding, Alex Raymond Renner, Eliot Winer
      An open-source web-application, TouchTerrain, was developed to simplify the production of 3D-printable terrain models. Direct Digital Manufacturing (DDM) using 3D Printers can change how geoscientists, students, and stakeholders interact with 3D data, with the potential to improve geoscience communication and environmental literacy. No other manufacturing technology can convert digital data into tangible objects quickly at relatively low cost; however, the expertise necessary to produce a 3D-printed terrain model can be a substantial burden: knowledge of geographical information systems, computer aided design (CAD) software, and 3D printers may all be required. Furthermore, printing models larger than the build volume of a 3D printer can pose further technical hurdles. The TouchTerrain web-application simplifies DDM for elevation data by generating digital 3D models customized for a specific 3D printer's capabilities. The only required user input is the selection of a region-of-interest using the provided web-application with a Google Maps-style interface. Publically available digital elevation data is processed via the Google Earth Engine API. To allow the manufacture of 3D terrain models larger than a 3D printer's build volume the selected area can be split into multiple tiles without third-party software. This application significantly reduces the time and effort required for a non-expert like an educator to obtain 3D terrain models for use in class. The web application is deployed at, while source code and installation instructions for a server and a stand-alone version are available at Github:

      PubDate: 2017-08-03T07:30:56Z
  • Iterative refinement of implicit boundary models for improved geological
           feature reproduction
    • Abstract: Publication date: Available online 21 July 2017
      Source:Computers & Geosciences
      Author(s): Ryan Martin, Jeff Boisvert
      Geological domains contain non-stationary features that cannot be described by a single direction of continuity. Non-stationary estimation frameworks generate more realistic curvilinear interpretations of subsurface geometries. A radial basis function (RBF) based implicit modeling framework using domain decomposition is developed that permits introduction of locally varying orientations and magnitudes of anisotropy for boundary models to better account for the local variability of complex geological deposits. The interpolation framework is paired with a method to automatically infer the locally predominant orientations, which results in a rapid and robust iterative non-stationary boundary modeling technique that can refine locally anisotropic geological shapes automatically from the sample data. The method also permits quantification of the volumetric uncertainty associated with the boundary modeling. The methodology is demonstrated on a porphyry dataset and shows improved local geological features.

      PubDate: 2017-07-22T20:27:40Z
  • Guided SAR image despeckling with probabilistic non local weights
    • Abstract: Publication date: Available online 21 July 2017
      Source:Computers & Geosciences
      Author(s): Jithin Gokul, Madhu S. Nair, Jeny Rajan
      SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

      PubDate: 2017-07-22T20:27:40Z
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