The gridding methods in Surfer allow you to produce accurate contour, surface, wireframe, vector, image, and shaded relief maps from your XYZ data. The data can be randomly dispersed over the map area, and Surfer's gridding will interpolate your data onto a grid. Use Surfer's default settings or choose from twelve different gridding methods.

Each gridding method provides complete control over the gridding parameters, so you can produce exactly the map you want. If your data are already collected in a regularly spaced rectangular array, you can create a map directly from your data. Computer generated contour maps have never been more accurate.

Gridding Features

• Interpolate up to 1 billion XYZ data points (limited by available memory)
• XYZ data can be any numeric data, include dates and times
• Grid the Z data as it is with linear values, or grid the logarithm of the Z data and save the grid with logarithmic Z values or convert the Z data back to linear
• Choose to limit the Z range in the generated grid file to the data limits or a custom value
• Automatically blank the area outside the convex hull of the data, and specify a buffer around the convex hull
• Set the grid line geometry including the XY grid limits, spacing between grid nodes, and the number of grid nodes
  grids with up to 2 billion nodes
• Use data exclusion filters to eliminate unwanted data
• Use duplicate data resolution techniques
• Generate a report of the gridding statistics and parameters including ANOVA regression statistics
• Use cross-validation to judge the suitability of the gridding method for the particular data set

Gridding Methods and Advanced Options

• Choose from one of the powerful gridding methods: Inverse Distance, Kriging, Minimum Curvature, Polynomial Regression, Triangulation with Linear Interpolation, Nearest Neighbor, Modified Shepard's Method, Radial Basis Function, Natural Neighbor, Moving Average, Data Metrics and Local Polynomial
• Use Nearest Neighbor to create grid files without interpolation
• Use Triangulation to achieve accuracy with large data sets faster
• Detrend a surface using Polynomial Regression, generate regression coefficients in a report, and calculate residuals
• Calculate grids with Data Metrics including: number of points within search ellipse, density of points within the search, distance to nearest and farthest neighbor, median, average and offset distance to points within the search ellipse
• Specify faults and breaklines when gridding
• Specify isotropic or anisotropic weighting
• Customize search options based on user-defined data sector parameters
• Specify search ellipses at any orientation and scaling
• Generate a grid of Kriging standard deviations
• Specify point or block Kriging
• Specify scales and range for each variogram model
• Generate grids from a user-specified function of two variables

Set the gridding parameters in the Grid Data dialog.