Results 171 to 180 of about 4,118 (206)

Semivariogram Models Based on Geometric Offsets

Mathematical Geology, 2006
Kriging-based geostatistical models require a semivariogram model. Next to the initial decision of stationarity, the choice of an appropriate semivariogram model is the most important decision in a geostatistical study. Common practice consists of fitting experimental semivariograms with a nested combination of proven models such as the spherical ...
Michael J. Pyrcz, Clayton V. Deutsch
openaire   +1 more source

The Effects of Influential Observations on Sample Semivariograms

Journal of Agricultural, Biological, and Environmental Statistics, 1997
Optimal prediction of the values of regionalized variables or the means of random fields is often accomplished by using kriging methods. These methods rely on satisfactory estimation of the underlying spatial semivariograms and the fitting of semivariogram models.
Sabyasachi Basu, Richard F. Gunst, Elizabeth A. Guertal, Molly I. Hartfield   +3 more
openaire   +1 more source

Characterization of alluvial hydrostratigraphy with indicator semivariograms

Water Resources Research, 1995
Current trends in hydrogeology seek to enlist sedimentary concepts in the interpretation of permeability structures. However, depositional models tend to account insufficiently for heterogeneities caused by complex controls on sediment preservation. Conversely, geostatistical methods empirically describe both random and structured attributes.
openaire   +1 more source

Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units

Mathematical Geosciences, 2007
This paper presents a methodology to conduct geostatistical variography and interpolation on areal data measured over geographical units (or blocks) with different sizes and shapes, while accounting for heterogeneous weight or kernel functions within those units.
openaire   +3 more sources

Scale Detection Using Semivariograms and Autocorrelograms

2006
The evolution and ecology of all organisms are contingent on the complex variation seen in nature. Landscape ecology differs from most other branches of ecology in that it explicitly involves spatial variation. Therefore, one of the goals of landscape ecology is to describe spatial variation. The purpose of this exercise is to.
openaire   +1 more source

An Algorithm for Sampling Optimization for Semivariogram Estimation

1995
This paper describes an algorithm for the optimal selection of sampling locations for semivariogram estimation. We assume that the semivariogram is estimated by fitting a parametric function of separation distance between observation sites to a selected subset of the squared differences of original observations (thereby restricting ourselves to ...
Werner G. Müller, Dale L. Zimmerman
openaire   +1 more source

Statistical Inference of the Semivariogram and the Quadratic Model

1984
Since the semi-variogram is the basic tool on Geostatistics, the following question appear inmediately: is it possible to find an accurate estimation of a semi-variogram from a single spatial outcome of a random function?
openaire   +1 more source

Sampling for estimating the semivariogram

2022
openaire   +2 more sources

Semivariogram fitting with linear programming

Computers & Geosciences, 2001
Yongliang Chen, Xiguo Jiao
openaire   +1 more source

Semivariogram estimation: asymptotic theory and applications

2016
The semivariogram is a function characterizing the second-order dependence structure of an intrinsically stationary random field; its estimation has applications in spatial statistics, particularly in the construction of optimal predictors of the random field at unobserved locations.
openaire   +1 more source