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  Subjects -> ENGINEERING (Total: 2287 journals)
    - CHEMICAL ENGINEERING (192 journals)
    - CIVIL ENGINEERING (186 journals)
    - ELECTRICAL ENGINEERING (105 journals)
    - ENGINEERING (1206 journals)
    - ENGINEERING MECHANICS AND MATERIALS (385 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (68 journals)
    - MECHANICAL ENGINEERING (90 journals)

ENGINEERING (1206 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: 19)
AAPG Bulletin     Hybrid Journal   (Followers: 6)
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: 234)
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: 7)
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: 25)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 15)
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: 21)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 28)
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: 37)
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: 30)
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: 16)
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: 15)
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  
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)
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: 4)
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: 31)
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  
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: 3)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 14)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 41)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 3)
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: 6)
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: 21)
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: 3)
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: 259)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 181)
Composites Part B : Engineering     Hybrid Journal   (Followers: 236)
Composites Science and Technology     Hybrid Journal   (Followers: 216)
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: 6)
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: 6)
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  
CTheory     Open Access  
Current Applied Physics     Full-text available via subscription   (Followers: 4)
Current Science     Open Access   (Followers: 58)

        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  [3044 journals]
  • A novel orthoimage mosaic method using the weighted A* algorithm for UAV
           imagery
    • 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
           p-normal
    • 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
       
  • A synthetic visual plane algorithm for visibility computation in
           consideration of accuracy and efficiency
    • Abstract: Publication date: Available online 18 September 2017
      Source:Computers & Geosciences
      Author(s): Jieqing Yu, Lixin Wu, Qingsong Hu, Zhigang Yan, Shaoliang Zhang
      Visibility computation is of great interest to location optimization, environmental planning, ecology, and tourism. Many algorithms have been developed for visibility computation. In this paper, we propose a novel method of visibility computation, called synthetic visual plane (SVP), to achieve better performance with respect to efficiency, accuracy, or both. The method uses a global horizon, which is a synthesis of line-of-sight information of all nearer points, to determine the visibility of a point, which makes it an accurate visibility method. We used discretization of horizon to gain a good performance in efficiency. After discretization, the accuracy and efficiency of SVP depends on the scale of discretization (i.e., zone width). The method is more accurate at smaller zone widths, but this requires a longer operating time. Users must strike a balance between accuracy and efficiency at their discretion. According to our experiments, SVP is less accurate but more efficient than R2 if the zone width is set to one grid. However, SVP becomes more accurate than R2 when the zone width is set to 1/24 grid, while it continues to perform as fast or faster than R2. Although SVP performs worse than reference plane and depth map with respect to efficiency, it is superior in accuracy to these other two algorithms.

      PubDate: 2017-09-20T06:44:46Z
       
  • Rapid earthquake detection through GPU-Based template matching
    • Abstract: Publication date: Available online 18 September 2017
      Source:Computers & Geosciences
      Author(s): Dawei Mu, En-Jui Lee, Po Chen
      The template-matching algorithm (TMA) has been widely adopted for improving the reliability of earthquake detection. The TMA is based on calculating the normalized cross-correlation coefficient (NCC) between a collection of selected template waveforms and the continuous waveform recordings of seismic instruments. In realistic applications, the computational cost of the TMA is much higher than that of traditional techniques. In this study, we provide an analysis of the TMA and show how the GPU architecture provides an almost ideal environment for accelerating the TMA and NCC-based pattern recognition algorithms in general. So far, our best-performing GPU code has achieved a speedup factor of more than 800 with respect to a common sequential CPU code. We demonstrate the performance of our GPU code using seismic waveform recordings from the ML 6.6 Meinong earthquake sequence in Taiwan.

      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
       
  • GSpecDisp: A matlab GUI package for phase-velocity dispersion measurements
           from ambient-noise correlations
    • Abstract: Publication date: Available online 14 September 2017
      Source:Computers & Geosciences
      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: https://github.com/Hamzeh-Sadeghi/GSpecDisp.

      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
       
  • Parallelization of interpolation, solar radiation and water flow
           simulation modules in GRASS GIS using OpenMP
    • Abstract: Publication date: October 2017
      Source:Computers & Geosciences, Volume 107
      Author(s): Jaroslav Hofierka, Michal Lacko, Stanislav Zubal
      In this paper, we describe the parallelization of three complex and computationally intensive modules of GRASS GIS using the OpenMP application programming interface for multi-core computers. These include the v.surf.rst module for spatial interpolation, the r.sun module for solar radiation modeling and the r.sim.water module for water flow simulation. We briefly describe the functionality of the modules and parallelization approaches used in the modules. Our approach includes the analysis of the module's functionality, identification of source code segments suitable for parallelization and proper application of OpenMP parallelization code to create efficient threads processing the subtasks. We document the efficiency of the solutions using the airborne laser scanning data representing land surface in the test area and derived high-resolution digital terrain model grids. We discuss the performance speed-up and parallelization efficiency depending on the number of processor threads. The study showed a substantial increase in computation speeds on a standard multi-core computer while maintaining the accuracy of results in comparison to the output from original modules. The presented parallelization approach showed the simplicity and efficiency of the parallelization of open-source GRASS GIS modules using OpenMP, leading to an increased performance of this geospatial software on standard multi-core computers.

      PubDate: 2017-09-08T08:50:56Z
       
  • WASS: An open-source pipeline for 3D stereo reconstruction of ocean waves
    • Abstract: Publication date: October 2017
      Source:Computers & Geosciences, Volume 107
      Author(s): Filippo Bergamasco, Andrea Torsello, Mauro Sclavo, Francesco Barbariol, Alvise Benetazzo
      Stereo 3D reconstruction of ocean waves is gaining more and more popularity in the oceanographic community and industry. Indeed, recent advances of both computer vision algorithms and computer processing power now allow the study of the spatio-temporal wave field with unprecedented accuracy, especially at small scales. Even if simple in theory, multiple details are difficult to be mastered for a practitioner, so that the implementation of a sea-waves 3D reconstruction pipeline is in general considered a complex task. For instance, camera calibration, reliable stereo feature matching and mean sea-plane estimation are all factors for which a well designed implementation can make the difference to obtain valuable results. For this reason, we believe that the open availability of a well tested software package that automates the reconstruction process from stereo images to a 3D point cloud would be a valuable addition for future researches in this area. We present WASS (http://www.dais.unive.it/wass), an Open-Source stereo processing pipeline for sea waves 3D reconstruction. Our tool completely automates all the steps required to estimate dense point clouds from stereo images. Namely, it computes the extrinsic parameters of the stereo rig so that no delicate calibration has to be performed on the field. It implements a fast 3D dense stereo reconstruction procedure based on the consolidated OpenCV library and, lastly, it includes set of filtering techniques both on the disparity map and the produced point cloud to remove the vast majority of erroneous points that can naturally arise while analyzing the optically complex nature of the water surface. In this paper, we describe the architecture of WASS and the internal algorithms involved. The pipeline workflow is shown step-by-step and demonstrated on real datasets acquired at sea.

      PubDate: 2017-09-08T08:50:56Z
       
  • Methods to enhance seismic faults and construct fault surfaces
    • Abstract: Publication date: October 2017
      Source:Computers & Geosciences, Volume 107
      Author(s): Xinming Wu, Zhihui Zhu
      Faults are often apparent as reflector discontinuities in a seismic volume. Numerous types of fault attributes have been proposed to highlight fault positions from a seismic volume by measuring reflection discontinuities. These attribute volumes, however, can be sensitive to noise and stratigraphic features that are also apparent as discontinuities in a seismic volume. We propose a matched filtering method to enhance a precomputed fault attribute volume, and simultaneously estimate fault strikes and dips. In this method, a set of efficient 2D exponential filters, oriented by all possible combinations of strike and dip angles, are applied to the input attribute volume to find the maximum filtering responses at all samples in the volume. These maximum filtering responses are recorded to obtain the enhanced fault attribute volume while the corresponding strike and dip angles, that yield the maximum filtering responses, are recoded to obtain volumes of fault strikes and dips. By doing this, we assume that a fault surface is locally planar, and a 2D smoothing filter will yield a maximum response if the smoothing plane coincides with a local fault plane. With the enhanced fault attribute volume and the estimated fault strike and dip volumes, we then compute oriented fault samples on the ridges of the enhanced fault attribute volume, and each sample is oriented by the estimated fault strike and dip. Fault surfaces can be constructed by directly linking the oriented fault samples with consistent fault strikes and dips. For complicated cases with missing fault samples and noisy samples, we further propose to use a perceptual grouping method to infer fault surfaces that reasonably fit the positions and orientations of the fault samples. We apply these methods to 3D synthetic and real examples and successfully extract multiple intersecting fault surfaces and complete fault surfaces without holes.

      PubDate: 2017-09-08T08:50:56Z
       
  • LSHSIM: A Locality Sensitive Hashing based method for multiple-point
           geostatistics
    • Abstract: Publication date: October 2017
      Source:Computers & Geosciences, Volume 107
      Author(s): Pedro Moura, Eduardo Laber, Hélio Lopes, Daniel Mesejo, Lucas Pavanelli, João Jardim, Francisco Thiesen, Gabriel Pujol
      Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.

      PubDate: 2017-09-08T08:50:56Z
       
  • Nurturing a growing field: Computers & Geosciences
    • Abstract: Publication date: October 2017
      Source:Computers & Geosciences, Volume 107
      Author(s): Gregoire Mariethoz, Edzer Pebesma


      PubDate: 2017-09-08T08:50:56Z
       
  • Finite-element time-domain modeling of electromagnetic data in general
           dispersive medium using adaptive Padé series
    • Abstract: Publication date: Available online 3 September 2017
      Source:Computers & Geosciences
      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: 2017-09-08T08:50:56Z
       
  • 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
           application
    • 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
       
  • HERA: A dynamic web application for visualizing community exposure to
           flood hazards based on storm and sea level rise scenarios
    • Abstract: Publication date: December 2017
      Source:Computers & Geosciences, Volume 109
      Author(s): Jeanne M. Jones, Kevin Henry, Nathan Wood, Peter Ng, Matthew Jamieson
      The Hazard Exposure Reporting and Analytics (HERA) dynamic web application was created to provide a platform that makes research on community exposure to coastal-flooding hazards influenced by sea level rise accessible to planners, decision makers, and the public in a manner that is both easy to use and easily accessible. HERA allows users to (a) choose flood-hazard scenarios based on sea level rise and storm assumptions, (b) appreciate the modeling uncertainty behind a chosen hazard zone, (c) select one or several communities to examine exposure, (d) select the category of population or societal asset, and (e) choose how to look at results. The application is designed to highlight comparisons between (a) varying levels of sea level rise and coastal storms, (b) communities, (c) societal asset categories, and (d) spatial scales. Through a combination of spatial and graphical visualizations, HERA aims to help individuals and organizations to craft more informed mitigation and adaptation strategies for climate-driven coastal hazards. This paper summarizes the technologies used to maximize the user experience, in terms of interface design, visualization approaches, and data processing.

      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
           models
    • 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 http://touchterrain.geol.iastate.edu, while source code and installation instructions for a server and a stand-alone version are available at Github: https://github.com/ChHarding/TouchTerrain_for_CAGEO.

      PubDate: 2017-08-03T07:30:56Z
       
  • Computation of fluid flow and pore-space properties estimation on micro-CT
           images of rock samples
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): M. Starnoni, D. Pokrajac, J.E. Neilson
      Accurate determination of the petrophysical properties of rocks, namely REV, mean pore and grain size and absolute permeability, is essential for a broad range of engineering applications. Here, the petrophysical properties of rocks are calculated using an integrated approach comprising image processing, statistical correlation and numerical simulations. The Stokes equations of creeping flow for incompressible fluids are solved using the Finite-Volume SIMPLE algorithm. Simulations are then carried out on three-dimensional digital images obtained from micro-CT scanning of two rock formations: one sandstone and one carbonate. Permeability is predicted from the computed flow field using Darcy's law. It is shown that REV, REA and mean pore and grain size are effectively estimated using the two-point spatial correlation function. Homogeneity and anisotropy are also evaluated using the same statistical tools. A comparison of different absolute permeability estimates is also presented, revealing a good agreement between the numerical value and the experimentally determined one for the carbonate sample, but a large discrepancy for the sandstone. Finally, a new convergence criterion for the SIMPLE algorithm, and more generally for the family of pressure-correction methods, is presented. This criterion is based on satisfaction of bulk momentum balance, which makes it particularly useful for pore-scale modelling of reservoir rocks.

      PubDate: 2017-07-22T20:27:40Z
       
  • Natural-color maps via coloring of bivariate grid data
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Jane E. Darbyshire, Bernhard Jenny
      Natural ground color is useful for maps where a representation of the Earth's surface matters. Natural color schemes are less likely to be misinterpreted, as opposed to hypsometric color schemes, and are generally preferred by map readers. The creation of natural-c\olor maps was once limited to manual cartographic techniques, but they can now be created digitally with the aid of raster graphics editing software. However, the creation of natural-color maps still requires many steps, a significant time investment, and fairly detailed digital land cover information, which makes this technique impossible to apply to global web maps at medium and large scales. A particular challenge for natural-color map creation is adjusting colors with location to create smoothly blending transitions. Adjustments with location are required to show land cover transitions between climate zones with a natural appearance. This study takes the first step in automating the process in order to facilitate the creation of medium- and large-scale natural-color maps covering large areas. A coloring method based on two grid inputs is presented. Here, we introduce an algorithmic method and prototype software for creating maps with this technique. The prototype software allows the map author to interactively assign colors to design the appearance of the map. This software can generate web map tiles at a global level for medium and large scales. Example natural-color web maps created with this coloring technique are provided.

      PubDate: 2017-07-22T20:27:40Z
       
  • 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
       
  • An adjoint-free method to determine conditional nonlinear optimal
           perturbations
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Aleid Oosterwijk, Henk A. Dijkstra, Tristan van Leeuwen
      The analysis of the growth of initial perturbations in dynamical systems is an important aspect of predictability theory because it informs on error growth. The Conditional Nonlinear Optimal Perturbation (CNOP) method is an approach where the nonlinear growth of perturbations is determined over a certain lead time. The CNOPs can be found by a nonlinear constrained optimisation problem, which is typically solved using sequential quadratic programming (SQP), a routine that requires an adjoint model. Such adjoint models are not always available and hence we here study the performance of an adjoint-free optimisation method (COBYLA), in combination with a dimension reduction technique, to determine CNOPs. The new technique is applied to a quasi-geostrophic model of the wind-driven ocean circulation. We find that COBYLA is able to find good approximations of CNOPs, albeit at a higher computational cost than conventional adjoint-based methods.

      PubDate: 2017-07-09T04:53:19Z
       
  • A framework for simulation and inversion in electromagnetics
    • Abstract: Publication date: Available online 3 July 2017
      Source:Computers & Geosciences
      Author(s): Lindsey J. Heagy, Rowan Cockett, Seogi Kang, Gudni K. Rosenkjaer, Douglas W. Oldenburg
      Simulations and inversions of electromagnetic geophysical data are paramount for discerning meaningful information about the subsurface from these data. Depending on the nature of the source electromagnetic experiments may be classified as time-domain or frequency-domain. Multiple heterogeneous and sometimes anisotropic physical properties, including electrical conductivity and magnetic permeability, may need be considered in a simulation. Depending on what one wants to accomplish in an inversion, the parameters which one inverts for may be a voxel-based description of the earth or some parametric representation that must be mapped onto a simulation mesh. Each of these permutations of the electromagnetic problem has implications in a numerical implementation of the forward simulation as well as in the computation of the sensitivities, which are required when considering gradient-based inversions. This paper proposes a framework for organizing and implementing electromagnetic simulations and gradient-based inversions in a modular, extensible fashion. We take an object-oriented approach for defining and organizing each of the necessary elements in an electromagnetic simulation, including: the physical properties, sources, formulation of the discrete problem to be solved, the resulting fields and fluxes, and receivers used to sample to the electromagnetic responses. A corresponding implementation is provided as part of the open source simulation and parameter estimation project SimPEG (http://simpeg.xyz). The application of the framework is demonstrated through two synthetic examples and one field example. The first example shows the application of the common framework for 1D time domain and frequency domain inversions. The second is a field example that demonstrates a 1D inversion of electromagnetic data collected over the Bookpurnong Irrigation District in Australia. The final example is a 3D example which shows how the modular implementation is used to compute the sensitivity for a parametric model where a transmitter is positioned inside a steel cased well.

      PubDate: 2017-07-09T04:53:19Z
       
  • Wind wave analysis in depth limited water using OCEANLYZ, A MATLAB toolbox
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Arash Karimpour, Qin Chen
      There are a number of well established methods in the literature describing how to assess and analyze measured wind wave data. However, obtaining reliable results from these methods requires adequate knowledge on their behavior, strengths and weaknesses. A proper implementation of these methods requires a series of procedures including a pretreatment of the raw measurements, and adjustment and refinement of the processed data to provide quality assurance of the outcomes, otherwise it can lead to untrustworthy results. This paper discusses potential issues in these procedures, explains what parameters are influential for the outcomes and suggests practical solutions to avoid and minimize the errors in the wave results. The procedure of converting the water pressure data into the water surface elevation data, treating the high frequency data with a low signal-to-noise ratio, partitioning swell energy from wind sea, and estimating the peak wave frequency from the weighted integral of the wave power spectrum are described. Conversion and recovery of the data acquired by a pressure transducer, particularly in depth-limited water like estuaries and lakes, are explained in detail. To provide researchers with tools for a reliable estimation of wind wave parameters, the Ocean Wave Analyzing toolbox, OCEANLYZ, is introduced. The toolbox contains a number of MATLAB functions for estimation of the wave properties in time and frequency domains. The toolbox has been developed and examined during a number of the field study projects in Louisiana’s estuaries.

      PubDate: 2017-06-28T12:16:45Z
       
  • Automatic identification of watercourses in flat and engineered landscapes
           by computing the skeleton of a LiDAR point cloud
    • Abstract: Publication date: Available online 13 June 2017
      Source:Computers & Geosciences
      Author(s): Tom Broersen, Ravi Peters, Hugo Ledoux
      Drainage networks play a crucial role in protecting land against floods. It is therefore important to have an accurate map of the watercourses that form the drainage network. Previous work on the automatic identification of watercourses was typically based on grids, focused on natural landscapes, and used mostly the slope and curvature of the terrain. We focus in this paper on areas that are characterised by low-lying, flat, and engineered landscapes; these are characteristic to the Netherlands for instance. We propose a new methodology to identify watercourses automatically from elevation data, it uses solely a raw classified LiDAR point cloud as input. We show that by computing twice a skeleton of the point cloud — once in 2D and once in 3D — and that by using the properties of the skeletons we can identify most of the watercourses. We have implemented our methodology and tested it for three different soil types around Utrecht, the Netherlands. We were able to detect 98% of the watercourses for one soil type, and around 75% for the worst case, when we compared to a reference dataset that was obtained semi-automatically.

      PubDate: 2017-06-15T07:48:41Z
       
  • Subsetting hyperspectral core imaging data using a
           graphic-identification-based IDL program
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Jun-Ting Qiu, Chuan Zhang, Zhang-Fa Yu, Qing-Jun Xu, Ding Wu, Wei-Wei Li, Jia-Lei Yao
      This study presents an IDL program to subset hyperspectral drill core imagery automatically based on graphic identification. A HySpex SWIR-320m-e imager and drill cores from the Xiangshan uranium deposit were used to do an application test. Based on the HySpex images, we found that the ratio variation tolerance of 75%, minimum marker size of 37 pixel × 37 pixel (28mm × 28mm), and wavelength of 1141.3nm (band #30) are preferences for the IDL program. The results indicate that the IDL program subsets hyperspectral images with high accuracy and efficiency without consuming additional time during the scanning process. Additionally, deformation of the core box, the material from which the core box is made, and variation in the diameter of the drill core do not significantly affect the quality of the results.

      PubDate: 2017-06-11T07:43:44Z
       
  • Applicability of computer-aided comprehensive tool (LINDA: LINeament
           Detection and Analysis) and shaded digital elevation model for
           characterizing and interpreting morphotectonic features from lineaments
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Alaa Masoud, Katsuaki Koike
      Detection and analysis of linear features related to surface and subsurface structures have been deemed necessary in natural resource exploration and earth surface instability assessment. Subjectivity in choosing control parameters required in conventional methods of lineament detection may cause unreliable results. To reduce this ambiguity, we developed LINDA (LINeament Detection and Analysis), an integrated tool with graphical user interface in Visual Basic. This tool automates processes of detection and analysis of linear features from grid data of topography (digital elevation model; DEM), gravity and magnetic surfaces, as well as data from remote sensing imagery. A simple interface with five display windows forms a user-friendly interactive environment. The interface facilitates grid data shading, detection and grouping of segments, lineament analyses for calculating strike and dip and estimating fault type, and interactive viewing of lineament geometry. Density maps of the center and intersection points of linear features (segments and lineaments) are also included. A systematic analysis of test DEMs and Landsat 7 ETM+ imagery datasets in the North and South Eastern Deserts of Egypt is implemented to demonstrate the capability of LINDA and correct use of its functions. Linear features from the DEM are superior to those from the imagery in terms of frequency, but both linear features agree with location and direction of V-shaped valleys and dykes and reference fault data. Through the case studies, LINDA applicability is demonstrated to highlight dominant structural trends, which can aid understanding of geodynamic frameworks in any region.

      PubDate: 2017-06-11T07:43:44Z
       
  • A Relevancy Algorithm for Curating Earth Science Data around Phenomenon
    • Abstract: Publication date: Available online 10 June 2017
      Source:Computers & Geosciences
      Author(s): Manil Maskey, Rahul Ramachandran, Xiang Li, Amanda Weigel, Kaylin Bugbee, Patrick Gatlin, J.J. Miller
      Earth science data are being collected for various science needs and applications, processed using different algorithms at multiple resolutions and coverages, and then archived at different archiving centers for distribution and stewardship causing difficulty in data discovery. Curation, which typically occurs in museums, art galleries, and libraries, is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest. Curating data sets around topics or areas of interest addresses some of the data discovery needs in the field of Earth science, especially for unanticipated users of data. This paper describes a methodology to automate search and selection of data around specific phenomena. Different components of the methodology including the assumptions, the process, and the relevancy ranking algorithm are described. The paper makes two unique contributions to improving data search and discovery capabilities. First, the paper describes a novel methodology developed for automatically curating data around a topic using Earth science metadata records. Second, the methodology has been implemented as a stand-alone web service that is utilized to augment search and usability of data in a variety of tools.

      PubDate: 2017-06-11T07:43:44Z
       
  • A Feature Selection Approach towards Progressive Vector Transmission over
           the Internet
    • Abstract: Publication date: Available online 8 June 2017
      Source:Computers & Geosciences
      Author(s): Ru Miao, Jia Song, Min Feng
      WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

      PubDate: 2017-06-11T07:43:44Z
       
  • WFCatalog: a catalogue for seismological waveform data
    • Abstract: Publication date: Available online 8 June 2017
      Source:Computers & Geosciences
      Author(s): Luca Trani, Mathijs Koymans, Malcolm Atkinson, Reinoud Sleeman, Rosa Filgueira
      This paper reports advances in seismic waveform description and discovery leading to a new seismological service and presents the key steps in its design, implementation and adoption. This service, named WFCatalog, which stands for waveform catalogue, accommodates features of seismological waveform data. Therefore, it meets the need for seismologists to be able to select waveform data based on seismic waveform features as well as sensor geolocations and temporal specifications. We describe the collaborative design methods and the technical solution showing the central role of seismic feature catalogues in framing the technical and operational delivery of the new service. Also, we provide an overview of the complex environment wherein this endeavour is scoped and the related challenges discussed. As multi-disciplinary, multi-organisational and global collaboration is necessary to address today's challenges, canonical representations can provide a focus for collaboration and conceptual tools for agreeing directions. Such collaborations can be fostered and formalised by rallying intellectual effort into the design of novel scientific catalogues and the services that support them. This work offers an example of the benefits generated by involving cross-disciplinary skills (e.g. data and domain expertise) from the early stages of design, and by sustaining the engagement with the target community throughout the delivery and deployment process.

      PubDate: 2017-06-11T07:43:44Z
       
  • Optimal estimation of areal values of near-land-surface temperatures for
           testing global and local spatio-temporal trends
    • Abstract: Publication date: Available online 6 June 2017
      Source:Computers & Geosciences
      Author(s): Hong Wang, Eulogio Pardo-Igúzquiza, Peter A. Dowd, Yongguo Yang
      This paper provides a solution to the problem of estimating the mean value of near-land-surface temperature over a relatively large area (here, by way of example, applied to mainland Spain covering an area of around half a million square kilometres) from a limited number of weather stations covering a non-representative (biased) range of altitudes. As evidence mounts for altitude-dependent global warming, this bias is a significant problem when temperatures at high altitudes are under-represented. We correct this bias by using altitude as a secondary variable and using a novel clustering method for identifying geographical regions (clusters) that maximize the correlation between altitude and mean temperature. In addition, the paper provides an improved regression kriging estimator, which is optimally determined by the cluster analysis. The optimal areal values of near-land-surface temperature are used to generate time series of areal temperature averages in order to assess regional changes in temperature trends. The methodology is applied to records of annual mean temperatures over the period 1950-2011 across mainland Spain. The robust non-parametric Theil-Sen method is used to test for temperature trends in the regional temperature time series. Our analysis shows that, over the 62-year period of the study, 78% of mainland Spain has had a statistically significant increase in annual mean temperature.

      PubDate: 2017-06-11T07:43:44Z
       
  • Unsupervised feature learning for autonomous rock image classification
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Lei Shu, Kenneth McIsaac, Gordon R. Osinski, Raymond Francis
      Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

      PubDate: 2017-06-06T07:57:39Z
       
  • Stochastic simulation by image quilting of process-based geological models
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Júlio Hoffimann, Céline Scheidt, Adrian Barfod, Jef Caers
      Process-based modeling offers a way to represent realistic geological heterogeneity in subsurface models. The main limitation lies in conditioning such models to data. Multiple-point geostatistics can use these process-based models as training images and address the data conditioning problem. In this work, we further develop image quilting as a method for 3D stochastic simulation capable of mimicking the realism of process-based geological models with minimal modeling effort (i.e. parameter tuning) and at the same time condition them to a variety of data. In particular, we develop a new probabilistic data aggregation method for image quilting that bypasses traditional ad-hoc weighting of auxiliary variables. In addition, we propose a novel criterion for template design in image quilting that generalizes the entropy plot for continuous training images. The criterion is based on the new concept of voxel reuse—a stochastic and quilting-aware function of the training image. We compare our proposed method with other established simulation methods on a set of process-based training images of varying complexity, including a real-case example of stochastic simulation of the buried-valley groundwater system in Denmark.

      PubDate: 2017-06-06T07:57:39Z
       
  • Porosity estimation by semi-supervised learning with sparsely available
           labeled samples
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Luiz Alberto Lima, Nico Görnitz, Luiz Eduardo Varella, Marley Vellasco, Klaus-Robert Müller, Shinichi Nakajima
      This paper addresses the porosity estimation problem from seismic impedance volumes and porosity samples located in a small group of exploratory wells. Regression methods, trained on the impedance as inputs and the porosity as output labels, generally suffer from extremely expensive (and hence sparsely available) porosity samples. To optimally make use of the valuable porosity data, a semi-supervised machine learning method was proposed, Transductive Conditional Random Field Regression (TCRFR), showing good performance (Görnitz et al., 2017). TCRFR, however, still requires more labeled data than those usually available, which creates a gap when applying the method to the porosity estimation problem in realistic situations. In this paper, we aim to fill this gap by introducing two graph-based preprocessing techniques, which adapt the original TCRFR for extremely weakly supervised scenarios. Our new method outperforms the previous automatic estimation methods on synthetic data and provides a comparable result to the manual labored, time-consuming geostatistics approach on real data, proving its potential as a practical industrial tool.

      PubDate: 2017-06-06T07:57:39Z
       
  • Computationally efficient variable resolution depth estimation
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): B.R. Calder, G. Rice
      A new algorithm for data-adaptive, large-scale, computationally efficient estimation of bathymetry is proposed. The algorithm uses a first pass over the observations to construct a spatially varying estimate of data density, which is then used to predict achievable estimate sample spacing for robust depth estimation across the area of interest. A low-resolution estimate of depth is also constructed during the first pass as a guide for further work. A piecewise-regular grid is then constructed following the sample spacing estimates, and accurate depth is finally estimated using the composite refined grid and an extended and re-implemented version of the cube algorithm. Resource-efficient data structures allow for the algorithm to operate over large areas and large datasets without excessive compute resources; modular design allows for more complex spatial representations to be included if required. The proposed system is demonstrated on a pair of hydrographic datasets, illustrating the adaptation of the algorithm to different depth- and sensor-driven data densities. Although the algorithm was designed for bathymetric estimation, it could be readily used on other two dimensional scalar fields where variable data density is a driver.

      PubDate: 2017-06-06T07:57:39Z
       
  • Spatial coding-based approach for partitioning big spatial data in Hadoop
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Xiaochuang Yao, Mohamed F. Mokbel, Louai Alarabi, Ahmed Eldawy, Jianyu Yang, Wenju Yun, Lin Li, Sijing Ye, Dehai Zhu
      Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

      PubDate: 2017-06-06T07:57:39Z
       
  • Learning Characteristic Natural Gamma Shale Marker Signatures in Iron Ore
           deposits
    • Abstract: Publication date: Available online 4 June 2017
      Source:Computers & Geosciences
      Author(s): D. Nathan, P. Duuring, E.J. Holden, D. Wedge, T. Horrocks
      Uncertainty in the location of stratigraphic boundaries in stratiform deposits has a direct impact on the uncertainty of resource estimates. The interpretation of stratigraphic boundaries in banded iron formation (BIF)-hosted deposits in the Hamersley province of Western Australia is made by recognizing shale markers which have characteristic signatures from natural gamma wireline logs. This paper presents a novel application of a probabilistic sequential model, named a continuous profile model, which is capable of jointly modelling the uncertainty in the amplitude and alignment of characteristic signatures. We demonstrate the accuracy of this approach by comparing three models that incorporate varying intensities of distortion and alignment in their ability to correctly identify a shale band of the West Angelas member of the Wittenoom Formation which overlies the Marra Mamba Iron Formation in the Hamersley Basin. Our experiments show that the proposed approach recovers 98.72% of interpreted shale band intervals and importantly quantifies the uncertainty in scale and alignment that contribute to probabilistic interpretations of stratigraphic boundaries.

      PubDate: 2017-06-06T07:57:39Z
       
  • Modelling the interaction of aeolian and fluvial processes with a combined
           cellular model of sand dunes and river systems
    • Abstract: Publication date: September 2017
      Source:Computers & Geosciences, Volume 106
      Author(s): Baoli Liu, Tom J. Coulthard
      Aeolian and fluvial processes are important agents for shaping the surface of the Earth, but are largely studied in isolation despite there being many locations where both processes are acting together and influencing each other. Using field data to investigate fluvial-aeolian interactions is, however, hampered by our short length of record and low temporal resolution of observations. Here we use numerical modelling to investigate, for the first time, the interplay between aeolian (sand dunes) and fluvial (river channel) processes. This modelling is carried out by combining two existing cellular models of aeolian and fluvial processes that requires considerable consideration of the different process representation and time stepping used. The result is a fully coupled (in time and space) sand dune – river model. Over a thousand-year simulation the model shows how the migration of sand dunes is readily blocked by rivers, yet aeolian processes can push the channel downwind. Over time cyclic channel avulsions develop indicating that aeolian action on fluvial systems may play an important part in governing avulsion frequency, and thus alluvial architecture.

      PubDate: 2017-05-26T18:16:29Z
       
 
 
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