APPLICATION OF THE KRIGING METHOD FOR GRAVITY DATA INTERPOLATION

https://doi.org/10.48498/minmag.2025.242.6.002

This article examines the application of the kriging method for the interpolation of gravimetric data. Three approaches are analyzed – Ordinary Kriging, Universal Kriging, and Empirical Bayesian Kriging – with the aim of constructing spatially continuous models of gravity anomalies. The methodology is implemented using the ArcGIS Pro toolkit. Particular attention is given to comparing the interpolation accuracy based on cross-validation indicators, including root mean square error and mean prediction error. The results show that EBK and UK with a linear trend provide the highest accuracy under various data characteristics, especially in the presence of trends and sparse observations. Kriging demonstrates high robustness, interpretability, and adaptability to the spatial distribution of gravimetric measurements, making it an effective tool in gravimetry and geoid modeling.

A. Kenesbayeva, *E.I. Kuldeev, E.O. Shalenov, T.B. Nurpeissova