Results 161 to 170 of about 9,305 (198)
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Spectral Corrected Semivariogram Models
Mathematical Geology, 2006Fitting semivariograms with analytical models can be tedious and restrictive. There are many smooth functions that could be used for the semivariogram; however, arbitrary interpolation of the semivariogram will almost certainly create an invalid function.
Michael J. Pyrcz, Clayton V. Deutsch
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Computers & Geosciences, 2007
A practical problem of interest in remote sensing is to increase the spatial resolution of a coarse spatial resolution image by fusing the information of that image with another fine spatial resolution image (from the same sensor or from sensors on different satellites).
Pardo-Iguzquiza, E., Atkinson, P.M.
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A practical problem of interest in remote sensing is to increase the spatial resolution of a coarse spatial resolution image by fusing the information of that image with another fine spatial resolution image (from the same sensor or from sensors on different satellites).
Pardo-Iguzquiza, E., Atkinson, P.M.
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2016
(Semi)Variograms are usually discussed in the framework of stationary or intrinsically stationary processes. We retell here this piece of theory in the setting of generic Gaussian vectors and of Gaussian vectors with constant variance. We show how to reparametrize the distribution as a function of the variogram and how to characterise all the Gaussian ...
Pistone, Giovanni, Vicario, Grazia
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(Semi)Variograms are usually discussed in the framework of stationary or intrinsically stationary processes. We retell here this piece of theory in the setting of generic Gaussian vectors and of Gaussian vectors with constant variance. We show how to reparametrize the distribution as a function of the variogram and how to characterise all the Gaussian ...
Pistone, Giovanni, Vicario, Grazia
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Mathematical Geology, 1994
A good fining of the structural junction that describes the variability of a spatial phenomenon is an essential stage in the building of an accurate estimator by kriging. The technique of the integral of the semivariogram (ISV) makes it possible to find this structural function while overcoming the problem of grouping together the pairs of experimental
Fréderick Delay, Ghislain de Marsily
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A good fining of the structural junction that describes the variability of a spatial phenomenon is an essential stage in the building of an accurate estimator by kriging. The technique of the integral of the semivariogram (ISV) makes it possible to find this structural function while overcoming the problem of grouping together the pairs of experimental
Fréderick Delay, Ghislain de Marsily
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Thermal Evaluation to Identify Nodules Using Semivariogram Curves
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Thermography can contribute to the early diagnosis of tumors by identifying nodules that need to be analyzed. The objective of this paper was to verify possible semivariogram curves to identify the possible spatial behavior centered in the region with the nodule and capture the thermal behavioral information surroundings of this point.
C G, Grassmann +3 more
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Using Semivariogram Parameter Uncertainty in Hydrogeological Applications
Groundwater, 2009Abstract Geostatistical estimation (kriging) and geostatistical simulation are routinely used in ground water hydrology for optimal spatial interpolation and Monte Carlo risk assessment, respectively. Both techniques are based on a model of spatial variability (semivariogram or covariance) that generally is not known but must be ...
Eulogio, Pardo-Igúzquiza +3 more
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Hybrid Estimation of Semivariogram Parameters
Mathematical Geology, 2007Two widely used methods of semivariogram estimation are weighted least squares estimation and 4 maximum likelihood estimation. The former have certain computational advantages, whereas the 5 latter are more statistically efficient. We introduce and study a "hybrid" semivariogram estimation 6 procedure that combines weighted least squares estimation of ...
Hao Zhang, Dale L. Zimmerman
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Stochastic simulation of semivariograms
Journal of the International Association for Mathematical Geology, 1982The semivariogram obtained from simulated space series formed by an autoregressive (AR) process gives a ready explanation for most of the common types. Linear semivariograms arise from a random walk (Brownian motion) process while the transitive and exponential types are generated by an AR process of first order. The continuous (“Gaussian”) type arises
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2006
Abstract This chapter proposes some new methods for computing empirical semivariograms and covariances and for fitting semivariogram and covariance models to empirical data. Grid-based empirical semivariograms and covariances are described, in which the grid values are smoothed using triangular kernels.
A. Gribov +2 more
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Abstract This chapter proposes some new methods for computing empirical semivariograms and covariances and for fitting semivariogram and covariance models to empirical data. Grid-based empirical semivariograms and covariances are described, in which the grid values are smoothed using triangular kernels.
A. Gribov +2 more
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Regularization of a semivariogram
Computers & Geosciences, 1977Abstract The production of estimates using the technique of kriging, and the evaluation of the accuracy of these estimates depends completely on the production of a model for the semivariogram of the deposit. The process of choosing such a model can be complicated in practice by the bulk and geometry of the samples taken. Some aspects of this problem
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