ALGORITEM KRIGING ZA KARTIRANJE GRAVIMETRICNIH PODATKOV NA SEVERU ALŽIRIJE

In this context, we have performed a first step of data validation using the Kriging interpolation, this method was applied to a set of free-air anomalies reduced by the EGM08 geopotential model, from the test zone located in the north of Algeria, but the data were considered as values of an isotropic variable whose the variographic analysis depends only on the distances between points. [...]we have performed a computer application for interpolation and validation of gravimetric data by Kriging method, based on the algorithm for validation and grid generation of free-air anomalies, proposed in this article, where the results showed that the free-air anomaly is an isotropic variable which only depends on the distances between positions, and that the values resulting from interpolation are validated by the BGI grid, where the two maps generated one by interpolation and the other by the BGI grid are very similar to confirm the validity of the Kriging algorithm developed in this context. [...]interpolation by Kriging can be carried out and this is the subject of the third part, where interpolation is used as a tool for performing data validation and mapping the gravimetric anomaly. 2 VARIABLE DESCRIPTION This description aims at presenting the studied variable before proceeding to the study of the data distribution in the geographical space. The third part, which is the most cumbersome in terms of software programming, is designed to the data validation and grid interpolation. 3.1 Kriging Model The choice of the model therefore imposes the type of Kriging to be used in order to perform the interpolation (Goovaerts, 1999, Chilès and Delfiner, 2012, Cressie, 2015). [...]the structure of spatial correlation will be illuminated too and will be characterized in our case by the variogram.