Results 121 to 130 of about 1,675 (179)

Validation of Management Zones, Variability, and Spatial Distribution of the Physiological Quality of Soybean Seeds. [PDF]

Plants (Basel)
de Oliveira Filho MA, Santos ALC, Domingues RF, Melazzo GM, Pontes BS, da Silva RJ, Hurtado SMC, Catão HCRM.   +7 more
europepmc   +1 more source

Geostress in the Ordovician system of the northern segment of the Shunbei No. 4 fault zone based on finite element simulation. [PDF]

Sci Rep
Feng X, Qian Z, Zhou L, Huo S, Liu J.
europepmc   +1 more source

Integration of geospatial techniques and artificial neural networks for groundwater potential zonation in India. [PDF]

Sci Rep
Badapalli PK, Nakkala AB, Pujari PS, Gugulothu S, Kottala RB, Mannala P, Alkhuraiji WS, Thamaga KH, Zhran M.   +8 more
europepmc   +1 more source

Remote and Proximal Sensors Data Fusion: Digital Twins in Irrigation Management Zoning. [PDF]

Sensors (Basel)
Rodrigues H, Ceddia MB, Tassinari W, Vasques GM, Brandão ZN, Morais JPS, Oliveira RP, Neves ML, Tavares SRL.   +8 more
europepmc   +1 more source

A simple method to assess flood regulation supply in urban lawns. [PDF]

MethodsX
Pereira P, Inacio M, Kalinauskas M, Pinto L, Barcelo D, Bogunovic I.   +5 more
europepmc   +1 more source

A neural network-based automatic semi-variogram modeling approach for geomagnetic map construction in multi-source indoor and outdoor navigation. [PDF]

Sci Rep
Zhan C, Huang P, Xue B, Lan B.
europepmc   +1 more source

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The effect of drift on the experimental semivariogram

Journal of the International Association for Mathematical Geology, 1982
When 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
exaly   +2 more sources

Regularization of a semivariogram

Computers and Geosciences, 1977
Abstract 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
exaly   +2 more sources

On the modelling of sand bedforms using the semivariogram

Earth Surface Processes and Landforms, 1988
AbstractThis 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.
Keith Richards, André Robert
exaly   +2 more sources

The integral of the semivariogram: A powerful method for adjusting the semivariogram in geostatistics

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
openaire   +1 more source