Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-3161-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-3161-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
GSTools v1.3: a toolbox for geostatistical modelling in Python
Sebastian Müller
CORRESPONDING AUTHOR
Department of Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam, Germany
Lennart Schüler
Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam, Germany
Department of Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Center for Advanced Systems Understanding (CASUS), Görlitz, Germany
Alraune Zech
Department of Earth Sciences, Utrecht University, Utrecht, the Netherlands
Department of Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Falk Heße
Institute of Earth and Environmental Sciences, University of Potsdam, Potsdam, Germany
Department of Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Viewed
Total article views: 7,591 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Oct 2021)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
4,938 | 2,552 | 101 | 7,591 | 96 | 59 |
- HTML: 4,938
- PDF: 2,552
- XML: 101
- Total: 7,591
- BibTeX: 96
- EndNote: 59
Total article views: 4,848 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 12 Apr 2022)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
3,440 | 1,343 | 65 | 4,848 | 75 | 48 |
- HTML: 3,440
- PDF: 1,343
- XML: 65
- Total: 4,848
- BibTeX: 75
- EndNote: 48
Total article views: 2,743 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Oct 2021)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,498 | 1,209 | 36 | 2,743 | 21 | 11 |
- HTML: 1,498
- PDF: 1,209
- XML: 36
- Total: 2,743
- BibTeX: 21
- EndNote: 11
Viewed (geographical distribution)
Total article views: 7,591 (including HTML, PDF, and XML)
Thereof 7,111 with geography defined
and 480 with unknown origin.
Total article views: 4,848 (including HTML, PDF, and XML)
Thereof 4,565 with geography defined
and 283 with unknown origin.
Total article views: 2,743 (including HTML, PDF, and XML)
Thereof 2,546 with geography defined
and 197 with unknown origin.
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Cited
63 citations as recorded by crossref.
- Acoustic cognitive map–based navigation in echolocating bats A. Goldshtein et al. 10.1126/science.adn6269
- Diffusive‐Dispersive Isotope Fractionation of Chlorinated Ethenes in Groundwater: The Key Role of Incomplete Mixing and Its Multi‐Scale Effects H. Wienkenjohann et al. 10.1029/2022WR034041
- Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring A. Piter et al. 10.1007/s41064-024-00314-x
- Probabilistic risk assessment of hurricane-induced debris impacts on coastal transportation infrastructure K. Amini & J. Padgett 10.1016/j.ress.2023.109579
- Spatially Correlated Nuclear Magnetic Resonance Profiles as a Tool for Precision Agriculture R. Lamanna et al. 10.1021/acs.jafc.2c08265
- Stochastic control of geological carbon storage operations using geophysical monitoring and deep reinforcement learning K. Noh & A. Swidinsky 10.1016/j.ijggc.2024.104238
- Glide-snow avalanches: a mechanical, threshold-based release area model A. Fees et al. 10.5194/nhess-24-3387-2024
- C3NN: Cosmological Correlator Convolutional Neural Network an Interpretable Machine-learning Framework for Cosmological Analyses Z. Gong et al. 10.3847/1538-4357/ad582e
- Towards reusable building blocks for agent-based modelling and theory development U. Berger et al. 10.1016/j.envsoft.2024.106003
- Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics S. Khandoozi et al. 10.1016/j.cej.2024.153127
- Stochastic Periodic Microstructures for Multiscale Modelling of Heterogeneous Materials E. Ricketts 10.1007/s11242-024-02074-z
- Spatial variability characterization and modelling of 2.5D woven SiO2f/SiO2 composites H. Wang et al. 10.1016/j.compositesa.2023.107997
- Fuzzy membership function for weighting pairs in variographical analysis P. Masoudi 10.1016/j.spasta.2022.100717
- Catchment‐Scale Architecture of the Deep Critical Zone Revealed by Seismic Imaging S. Pasquet et al. 10.1029/2022GL098433
- A Physics-Informed Spatial-Temporal Neural Network for Reservoir Simulation and Uncertainty Quantification J. Bi et al. 10.2118/218386-PA
- Measuring the Unmeasurable: Models of Geographical Context A. Fotheringham & Z. Li 10.1080/24694452.2023.2227690
- Unsupervised deep network for image texture transformation: Improving the quality of cross-correlation analysis and mechanical vortex visualisation during cardiac fibrillation D. Mangileva et al. 10.1016/j.heliyon.2023.e22207
- Towards a new standard for seismic moment tensor inversion containing 3-D earth structure uncertainty T. Phạm et al. 10.1093/gji/ggae256
- An adaptive global–local generalized FEM for multiscale advection–diffusion problems L. He et al. 10.1016/j.cma.2023.116548
- Spatial Interpolation and Conditional Map Generation Using Deep Image Prior for Environmental Applications H. Rakotonirina et al. 10.1007/s11004-023-10125-2
- Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions Y. Hu et al. 10.1016/j.enggeo.2024.107445
- Effects of Spatial Variation in Relative Density on Seismic Behavior of Saturated Sandy Ground M. Sawatsubashi et al. 10.1142/S1793431124500180
- Pollution risk evaluation of groundwater wells based on stochastic and deterministic simulation of aquifer lithology W. Yang et al. 10.1016/j.ecoenv.2024.117027
- Risk assessment of municipal solid waste (MSW) dumps using two-phase Random SPH: case study of three dumpsites S. Mhaski & G. Ramana 10.1007/s40571-023-00627-5
- Integrated surrogate framework for reactive transport simulation of uranium in situ leaching with generative models W. Ji et al. 10.1016/j.jhydrol.2024.130737
- A Novel Framework and a New Score for the Comparative Analysis of Forest Models Accounting for the Impact of Climate Change N. Besic et al. 10.1007/s13253-023-00557-y
- Comparing 2D and 3D slope stability in spatially variable soils using random finite-element method C. WU et al. 10.1016/j.compgeo.2024.106324
- Predicting CO2-EOR and storage in low-permeability reservoirs with deep learning-based surrogate flow models S. Meng et al. 10.1016/j.geoen.2023.212467
- parafields: A generator for distributed, stationary Gaussian processes D. Kempf et al. 10.21105/joss.05735
- GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications G. Tang et al. 10.5194/gmd-17-1153-2024
- Conditioning of multiple-point statistics simulations to indirect geophysical data S. Levy et al. 10.1016/j.cageo.2024.105581
- GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation E. MacKie et al. 10.5194/gmd-16-3765-2023
- A novel deep learning-based automatic search workflow for CO2 sequestration surrogate flow models J. Xu et al. 10.1016/j.fuel.2023.129353
- An encoder-decoder ConvLSTM surrogate model for simulating geological CO2 sequestration with dynamic well controls Z. Feng et al. 10.1016/j.jgsce.2024.205314
- A Statistical Finite Element Method Integrating a Plurigaussian Random Field Generator for Multi-scale Modelling of Solute Transport in Concrete E. Ricketts et al. 10.1007/s11242-023-01930-8
- The influence of spatial variation on the design of foundations of immersed tunnels: Advanced probabilistic analysis C. ’t Hart et al. 10.1016/j.tust.2024.105624
- Optical dispersions through intracellular inhomogeneities M. Watabe et al. 10.1103/PhysRevResearch.5.L022043
- Time-dependent dispersion coefficients for the evolution of displacement fronts in heterogeneous porous media S. Tajima et al. 10.1016/j.advwatres.2024.104714
- Methods for Characterizing Groundwater Resources with Sparse In Situ Data R. Nishimura et al. 10.3390/hydrology9080134
- Comparison of Different Quantitative Precipitation Estimation Methods Based on a Severe Rainfall Event in Tuscany, Italy, November 2023 A. Biondi et al. 10.3390/rs16213985
- Seismic amplitude response to internal heterogeneity of mass-transport deposits J. Ford et al. 10.5194/se-14-137-2023
- Stability and reliability analysis of rock slope based on parameter conditioned random field K. Chen & Q. Jiang 10.1007/s10064-024-03799-3
- Demonstration of a Modular Prototype End-to-End Simulator for Aquatic Remote Sensing Applications M. Matthews et al. 10.3390/s23187824
- Decentralized Sparse Gaussian Process Regression with Event-Triggered Adaptive Inducing Points T. Norton et al. 10.1007/s10846-023-01894-3
- Impacts of Permeability Heterogeneity and Background Flow on Supercritical CO2 Dissolution in the Deep Subsurface S. Hansen et al. 10.1029/2023WR035394
- Influence of slab depth spatial variability on skier-triggering probability and avalanche size F. Meloche et al. 10.1017/aog.2024.3
- GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields P. Robbe 10.21105/joss.05595
- Building a framework for probabilistic assessment accounting for soil, spatial, operational and model uncertainty, applied to pile driveability T. Vergote & S. Raymackers 10.1016/j.oceaneng.2022.113181
- Quantifying variation in maximum floor accelerations of modular buildings under earthquakes through stochastic nonlinear structural analysis C. Wang & T. Chan 10.1016/j.tws.2023.111454
- Assessing Quantitative Precipitation Estimation Methods Based on the Fusion of Weather Radar and Rain-Gauge Data A. Biondi et al. 10.1109/LGRS.2024.3434650
- Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements E. Kanin et al. 10.1016/j.ptlrs.2024.09.001
- Relating defect concentrations to spatially fluctuating lattice strains A. Warwick et al. 10.1016/j.scriptamat.2024.116276
- Data-driven estimates for the geostatistical characterization of subsurface hydraulic properties F. Heße et al. 10.5194/hess-28-357-2024
- Deep transfer learning for groundwater flow in heterogeneous aquifers using a simple analytical model J. Zhang et al. 10.1016/j.jhydrol.2023.130293
- Discrete modeling of elastic heterogeneous media Q. Zhang et al. 10.1016/j.mechrescom.2024.104277
- Uncertainty Quantification of Contaminated Soil Volume with Deep Neural Networks and Predictive Models I. Guridi et al. 10.1007/s10666-023-09924-y
- Measuring basin-scale aquifer storage change and mapping specific yield in Albuquerque, New Mexico, USA, with repeat microgravity data J. Kennedy & M. Bell 10.1016/j.ejrh.2023.101413
- Modeling drug transport and absorption in subcutaneous injection of monoclonal antibodies: Impact of tissue deformation, devices, and physiology M. de Lucio et al. 10.1016/j.ijpharm.2024.124446
- Should We Worry About Surficial Dynamics When Assessing Nutrient Cycling in the Groundwater? S. Khurana et al. 10.3389/frwa.2022.780297
- SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python M. Mälicke 10.5194/gmd-15-2505-2022
- Updating reliability of pile groups with load tests considering spatially variable soils Y. Zhang et al. 10.1080/17499518.2024.2328189
- Predicting the impact of spatial heterogeneity on microbially mediated nutrient cycling in the subsurface S. Khurana et al. 10.5194/bg-19-665-2022
- Fuzzy membership function for weighting pairs in variographical analysis P. Masoudi 10.1016/j.spasta.2022.100717
58 citations as recorded by crossref.
- Acoustic cognitive map–based navigation in echolocating bats A. Goldshtein et al. 10.1126/science.adn6269
- Diffusive‐Dispersive Isotope Fractionation of Chlorinated Ethenes in Groundwater: The Key Role of Incomplete Mixing and Its Multi‐Scale Effects H. Wienkenjohann et al. 10.1029/2022WR034041
- Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring A. Piter et al. 10.1007/s41064-024-00314-x
- Probabilistic risk assessment of hurricane-induced debris impacts on coastal transportation infrastructure K. Amini & J. Padgett 10.1016/j.ress.2023.109579
- Spatially Correlated Nuclear Magnetic Resonance Profiles as a Tool for Precision Agriculture R. Lamanna et al. 10.1021/acs.jafc.2c08265
- Stochastic control of geological carbon storage operations using geophysical monitoring and deep reinforcement learning K. Noh & A. Swidinsky 10.1016/j.ijggc.2024.104238
- Glide-snow avalanches: a mechanical, threshold-based release area model A. Fees et al. 10.5194/nhess-24-3387-2024
- C3NN: Cosmological Correlator Convolutional Neural Network an Interpretable Machine-learning Framework for Cosmological Analyses Z. Gong et al. 10.3847/1538-4357/ad582e
- Towards reusable building blocks for agent-based modelling and theory development U. Berger et al. 10.1016/j.envsoft.2024.106003
- Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics S. Khandoozi et al. 10.1016/j.cej.2024.153127
- Stochastic Periodic Microstructures for Multiscale Modelling of Heterogeneous Materials E. Ricketts 10.1007/s11242-024-02074-z
- Spatial variability characterization and modelling of 2.5D woven SiO2f/SiO2 composites H. Wang et al. 10.1016/j.compositesa.2023.107997
- Fuzzy membership function for weighting pairs in variographical analysis P. Masoudi 10.1016/j.spasta.2022.100717
- Catchment‐Scale Architecture of the Deep Critical Zone Revealed by Seismic Imaging S. Pasquet et al. 10.1029/2022GL098433
- A Physics-Informed Spatial-Temporal Neural Network for Reservoir Simulation and Uncertainty Quantification J. Bi et al. 10.2118/218386-PA
- Measuring the Unmeasurable: Models of Geographical Context A. Fotheringham & Z. Li 10.1080/24694452.2023.2227690
- Unsupervised deep network for image texture transformation: Improving the quality of cross-correlation analysis and mechanical vortex visualisation during cardiac fibrillation D. Mangileva et al. 10.1016/j.heliyon.2023.e22207
- Towards a new standard for seismic moment tensor inversion containing 3-D earth structure uncertainty T. Phạm et al. 10.1093/gji/ggae256
- An adaptive global–local generalized FEM for multiscale advection–diffusion problems L. He et al. 10.1016/j.cma.2023.116548
- Spatial Interpolation and Conditional Map Generation Using Deep Image Prior for Environmental Applications H. Rakotonirina et al. 10.1007/s11004-023-10125-2
- Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions Y. Hu et al. 10.1016/j.enggeo.2024.107445
- Effects of Spatial Variation in Relative Density on Seismic Behavior of Saturated Sandy Ground M. Sawatsubashi et al. 10.1142/S1793431124500180
- Pollution risk evaluation of groundwater wells based on stochastic and deterministic simulation of aquifer lithology W. Yang et al. 10.1016/j.ecoenv.2024.117027
- Risk assessment of municipal solid waste (MSW) dumps using two-phase Random SPH: case study of three dumpsites S. Mhaski & G. Ramana 10.1007/s40571-023-00627-5
- Integrated surrogate framework for reactive transport simulation of uranium in situ leaching with generative models W. Ji et al. 10.1016/j.jhydrol.2024.130737
- A Novel Framework and a New Score for the Comparative Analysis of Forest Models Accounting for the Impact of Climate Change N. Besic et al. 10.1007/s13253-023-00557-y
- Comparing 2D and 3D slope stability in spatially variable soils using random finite-element method C. WU et al. 10.1016/j.compgeo.2024.106324
- Predicting CO2-EOR and storage in low-permeability reservoirs with deep learning-based surrogate flow models S. Meng et al. 10.1016/j.geoen.2023.212467
- parafields: A generator for distributed, stationary Gaussian processes D. Kempf et al. 10.21105/joss.05735
- GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications G. Tang et al. 10.5194/gmd-17-1153-2024
- Conditioning of multiple-point statistics simulations to indirect geophysical data S. Levy et al. 10.1016/j.cageo.2024.105581
- GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation E. MacKie et al. 10.5194/gmd-16-3765-2023
- A novel deep learning-based automatic search workflow for CO2 sequestration surrogate flow models J. Xu et al. 10.1016/j.fuel.2023.129353
- An encoder-decoder ConvLSTM surrogate model for simulating geological CO2 sequestration with dynamic well controls Z. Feng et al. 10.1016/j.jgsce.2024.205314
- A Statistical Finite Element Method Integrating a Plurigaussian Random Field Generator for Multi-scale Modelling of Solute Transport in Concrete E. Ricketts et al. 10.1007/s11242-023-01930-8
- The influence of spatial variation on the design of foundations of immersed tunnels: Advanced probabilistic analysis C. ’t Hart et al. 10.1016/j.tust.2024.105624
- Optical dispersions through intracellular inhomogeneities M. Watabe et al. 10.1103/PhysRevResearch.5.L022043
- Time-dependent dispersion coefficients for the evolution of displacement fronts in heterogeneous porous media S. Tajima et al. 10.1016/j.advwatres.2024.104714
- Methods for Characterizing Groundwater Resources with Sparse In Situ Data R. Nishimura et al. 10.3390/hydrology9080134
- Comparison of Different Quantitative Precipitation Estimation Methods Based on a Severe Rainfall Event in Tuscany, Italy, November 2023 A. Biondi et al. 10.3390/rs16213985
- Seismic amplitude response to internal heterogeneity of mass-transport deposits J. Ford et al. 10.5194/se-14-137-2023
- Stability and reliability analysis of rock slope based on parameter conditioned random field K. Chen & Q. Jiang 10.1007/s10064-024-03799-3
- Demonstration of a Modular Prototype End-to-End Simulator for Aquatic Remote Sensing Applications M. Matthews et al. 10.3390/s23187824
- Decentralized Sparse Gaussian Process Regression with Event-Triggered Adaptive Inducing Points T. Norton et al. 10.1007/s10846-023-01894-3
- Impacts of Permeability Heterogeneity and Background Flow on Supercritical CO2 Dissolution in the Deep Subsurface S. Hansen et al. 10.1029/2023WR035394
- Influence of slab depth spatial variability on skier-triggering probability and avalanche size F. Meloche et al. 10.1017/aog.2024.3
- GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields P. Robbe 10.21105/joss.05595
- Building a framework for probabilistic assessment accounting for soil, spatial, operational and model uncertainty, applied to pile driveability T. Vergote & S. Raymackers 10.1016/j.oceaneng.2022.113181
- Quantifying variation in maximum floor accelerations of modular buildings under earthquakes through stochastic nonlinear structural analysis C. Wang & T. Chan 10.1016/j.tws.2023.111454
- Assessing Quantitative Precipitation Estimation Methods Based on the Fusion of Weather Radar and Rain-Gauge Data A. Biondi et al. 10.1109/LGRS.2024.3434650
- Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements E. Kanin et al. 10.1016/j.ptlrs.2024.09.001
- Relating defect concentrations to spatially fluctuating lattice strains A. Warwick et al. 10.1016/j.scriptamat.2024.116276
- Data-driven estimates for the geostatistical characterization of subsurface hydraulic properties F. Heße et al. 10.5194/hess-28-357-2024
- Deep transfer learning for groundwater flow in heterogeneous aquifers using a simple analytical model J. Zhang et al. 10.1016/j.jhydrol.2023.130293
- Discrete modeling of elastic heterogeneous media Q. Zhang et al. 10.1016/j.mechrescom.2024.104277
- Uncertainty Quantification of Contaminated Soil Volume with Deep Neural Networks and Predictive Models I. Guridi et al. 10.1007/s10666-023-09924-y
- Measuring basin-scale aquifer storage change and mapping specific yield in Albuquerque, New Mexico, USA, with repeat microgravity data J. Kennedy & M. Bell 10.1016/j.ejrh.2023.101413
- Modeling drug transport and absorption in subcutaneous injection of monoclonal antibodies: Impact of tissue deformation, devices, and physiology M. de Lucio et al. 10.1016/j.ijpharm.2024.124446
5 citations as recorded by crossref.
- Should We Worry About Surficial Dynamics When Assessing Nutrient Cycling in the Groundwater? S. Khurana et al. 10.3389/frwa.2022.780297
- SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python M. Mälicke 10.5194/gmd-15-2505-2022
- Updating reliability of pile groups with load tests considering spatially variable soils Y. Zhang et al. 10.1080/17499518.2024.2328189
- Predicting the impact of spatial heterogeneity on microbially mediated nutrient cycling in the subsurface S. Khurana et al. 10.5194/bg-19-665-2022
- Fuzzy membership function for weighting pairs in variographical analysis P. Masoudi 10.1016/j.spasta.2022.100717
Latest update: 20 Nov 2024
Short summary
The GSTools package provides a Python-based platform for geoostatistical applications. Salient features of GSTools are its random field generation, its kriging capabilities and its versatile covariance model. It is furthermore integrated with other Python packages, like PyKrige, ogs5py or scikit-gstat, and provides interfaces to meshio and PyVista. Four presented workflows showcase the abilities of GSTools.
The GSTools package provides a Python-based platform for geoostatistical applications. Salient...