A neural network-based automatic semi-variogram modeling approach for geomagnetic map construction in multi-source indoor and outdoor navigation [PDF]
Scientific ReportsHigh-precision geomagnetic maps are essential for geomagnetic-assisted navigation, yet their construction is constrained by kriging interpolation’s reliance on accurately modeled semi-variogram.
Chengsheng Zhan +3 more
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Journal of Hydrology X, 2019 When using a ground water elevation dataset for the development of a ground water model, it is prudent to first evaluate the quality of the data before using it in a ground water model.
Zane D. Helwig +3 more
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Inference for variograms [PDF]
Computational Statistics & Data Analysis, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bowman, A.W., Crujeiras, R.M.
openaire +4 more sources
Interpolation methods for spatial distribution of groundwater mapping electrical conductivity [PDF]
Scientific ReportsThis study was carried out to develop a conceptual framework for determining the best interpolation method which mainly is employed to calculate the variability maps of electrical conductivity (EC) in neighboring regions.
Saeed Salehi +4 more
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Evaluation of Spatio-Temporal Variogram Models for Mapping Xco2 Using Satellite Observations: A Case Study in China [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015 Greenhouse Gases Observing Satellite (GOSAT), which measures column-averaged carbon dioxide dry air mole fractions (Xco2) from space, provides new data sources to improve our understanding of carbon cycle.
Lijie Guo +5 more
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The textures of sarcoidosis: quantifying lung disease through variograms. [PDF]
Phys Med BiolLippitt WL +12 more
europepmc +2 more sources
SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python [PDF]
Geoscientific Model Development, 2022 Geostatistical methods are widely used in almost all geoscientific disciplines, i.e., for interpolation, rescaling, data assimilation or modeling. At its core, geostatistics aims to detect, quantify, describe, analyze and model spatial covariance of ...
M. Mälicke
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Research on variogram analysis method for 3D modeling of sandstone reservoir [PDF]
E3S Web of Conferences, 2023 Analysis of variogram is a necessary step in 3D stochastic modeling, and different settings of variograms can directly affect the final distribution of model attribute.
Lv Yingbo, Liang Yifei, Wang HongXue
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Spatial Prediction for Real Data using Kriging Technique [PDF]
المجلة العراقية للعلوم الاحصائية, 2018 This study investigates the prediction of unstable random spatial process using the Ordinary Kriging technique, based on the variogram function Y(X,Y) in finding out the predictors, and the universal multivariate technique, which has been applied by ...
Shaymaa Riyadh Thanoon Thanoon
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Anomaly detection in geostatistical models with application to groundwater level data in the Gaza Coastal Aquifer [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2022 In geostatistics, the detection of anomalous observations has a particular importance because of the changes they can create in environmental and geological patterns. Few methods for detecting such observations in univariate data have been proposed for
Ali H. Abuzaid +2 more
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