Results 161 to 170 of about 9,440 (213)
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The effect of drift on the experimental semivariogram
Journal of the International Association for Mathematical Geology, 1982When nonlinear drift is present, the nature of the bias in the experimental semivariogram estimator of the semivariogram function is determined by the extent and density of the sampling as well as by the drift function itself. The bias caused by drift may affect the interpretation of the experimental semivariogram over its entire range.
T. H. Starks, J. H. Fang
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Regularization of a semivariogram
Computers and 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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On the modelling of sand bedforms using the semivariogram
Earth Surface Processes and Landforms, 1988AbstractThis study shows the usefulness of the semivariogram for modelling sand ripples created by water flows of varied flow intensity. A combination of two mathematical functions is fitted to each sample semivariogram, that is an exponential (or stochastic) component and a periodic component.
André Robert, Keith RichardS
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Semivariogram modeling by weighted least squares
Computers and Geosciences, 1996Abstract Permissible semivariogram models are fundamental for geostatistical estimation and simulation of attributes having a continuous spatiotemporal variation. The usual practice is to fit those models manually to experimental semivariograms.
Ricardo A Olea, Yun-Sheng Yu
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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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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).
Eulogio Pardo-Igúzquiza +1 more
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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).
Eulogio Pardo-Igúzquiza +1 more
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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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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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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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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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