3D estimation of metal elements in sediments of the Caspian Sea with moving least square and radial basis function interpolation methods

Spatially continuous data is important in modeling numerical and computational works. Since sampling points are not continuous, interpolation methods should be used to estimate data at unsampled points. In this paper, Radial Basis Function (RBF) and Moving Least Square (MLS) interpolation methods are applied to estimate the concentrations of nickel, mercury, lead, copper, and chromium in the Caspian Sea by programming. Cross validation results are also obtained by RBF and MLS methods and have been compared for Lindane, total DDT, total HCH, total hydrocarbons and total PAH elements. Input data for MLS and RBF are longitudinal, latitude and depth (3D interpolation) at any point. Outputs of MLS and RBF are concentrations of an element at any point. A new method is introduced for dening a constant parameter in RBF. The number of sampling points for calibration and verication tests is analyzed with the values of Root Mean Square Error (RMSE) in pollutant parameters. Optimum selection of MLS parameters is used in this paper. The results of concentration estimation of metal elements in sediments of the Caspian Sea, by MLS and RBF, show that RBF method yields more accurate results than MLS method.