Grid method parameters control the interpolation procedures. You can usually accept the default gridding method and produce an acceptable map. Different gridding methods provide different interpretations of your data because each method calculates grid node values using a different algorithm. If you are not satisfied with the map of your data, you might consider producing maps using several different gridding methods and comparing the results.
Because contour, gradient, and vector maps are created from gridded data, the original data are not necessarily honored in the grid. If you post the original data on the map, some of the color levels might be positioned "wrong" relative to the original data. This happens because the locations of the color level boundaries are determined solely by the interpolated grid node values and not directly by the original data. Some methods are better than others in preserving your data, and sometimes some experimentation (i.e. increasing grid density) is necessary before you can determine the best method for your data.
Gridding methods are selected in the map's Gridding page . Gridding methods include Data Metrics, Inverse Distance to a Power, Kriging, Local Polynomial, Minimum Curvature, Modified Shepard's Method, Moving Average, Natural Neighbor, Nearest Neighbor, Polynomial Regression, Radial Basis Function, Triangulation with Border Color Interpolation, and Triangulation with Linear Interpolation.
See Also