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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Remote Sensing, 2012 A detailed introduction to variogram analysis of reflectance data is provided, and variogram parameters (nugget, sill, and range values) were examined as possible indicators of abiotic (irrigation regime) and biotic (spider mite infestation) stressors ...
Christian Nansen
exaly +3 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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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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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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Planning spatial sampling of the soil from an uncertain reconnaissance variogram [PDF]
SOIL, 2017 An estimated variogram of a soil property can be used to support a rational choice of sampling intensity for geostatistical mapping. However, it is known that estimated variograms are subject to uncertainty.
R. M. Lark +8 more
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On Robustness for Spatio-Temporal Data
Mathematics, 2022 The spatio-temporal variogram is an important factor in spatio-temporal prediction through kriging, especially in fields such as environmental sustainability or climate change, where spatio-temporal data analysis is based on this concept.
Alfonso García-Pérez
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Assessing the role of spatial externalities in the survival of Italian innovative startups
Regional Science Policy &Practice, EarlyView., 2023 Abstract The paper provides novel empirical evidence about the effects of spatial externalities on the survival of innovative startups in Italy. Using geocoded firm‐level data, we build micro‐geographic measures of specialization and diversity that are robust to the modifiable areal unit problem.
Diego Giuliani +4 more
wiley +1 more source
Application of Dueling DQN and DECGA for Parameter Estimation in Variogram Models
IEEE Access, 2020 Parameter estimation of variogram models is an important problem in geostatistics and environmental engineering. Most of existing works aim to estimate parameters of variogram single models, while neglecting the parameter estimation of variogram nested ...
Yu Liu, Cong Zhang
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