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Voxler has several different gridding methods available for the Gridder module. The differences between gridding methods are in the mathematical algorithms used to compute the weights during lattice node interpolation. Each method can result in a different representation of the data.
The gridding methods include:
- Inverse Distance to a Power - fast but has the tendency to generate concentric spheres around high and low values unless you increase the Smooth value. This method does not extrapolate beyond the Z range of the data.
- Local Polynomial - most applicable to data sets that are locally smooth, i.e., relatively smooth surfaces within the search neighborhoods. The computational speed of the method is not significantly affected by the size of the data set.
- Data Metrics - used to calculate statistics about a data set
Additional information about the gridding methods can be found in our online help.
Updated August 2, 2018