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 computationalworks. since sampling points are not continuous, interpolation methods shouldbe used to estimate data at unsampled points. in this paper, radial basis function(rbf) and moving least square (mls) interpolation methods are applied to estimatethe concentrations of nickel, mercury, lead, copper, and chromium in the caspian sea byprogramming. cross validation results are also obtained by rbf and mls methods andhave been compared for lindane, total ddt, total hch, total hydrocarbons and totalpah elements. input data for mls and rbf are longitudinal, latitude and depth (3dinterpolation) at any point. outputs of mls and rbf are concentrations of an elementat any point. a new method is introduced for dening a constant parameter in rbf. thenumber of sampling points for calibration and verication tests is analyzed with the valuesof root mean square error (rmse) in pollutant parameters. optimum selection of mlsparameters is used in this paper. the results of concentration estimation of metal elementsin sediments of the caspian sea, by mls and rbf, show that rbf method yields moreaccurate results than mls method.