Template:GMS 2D Interpolation Method: Difference between revisions
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*[[GMS:Kriging|Kriging]] – Based on the assumption that the parameter being interpolated can be treated as a regionalized variable. | *[[GMS:Kriging|Kriging]] – Based on the assumption that the parameter being interpolated can be treated as a regionalized variable. | ||
[[GMS:2D Interpolation Options#Log Interpolation|Log interpolation]] is also supported.<noinclude>[[Category:Interpolation]][[Category:2D Scatter Point]]</noinclude> | [[GMS:2D Interpolation Options#Log Interpolation|Log interpolation]] is also supported.<noinclude>[[Category:Interpolation|2D]][[Category:2D Scatter Point|Inter]]</noinclude> | ||
Latest revision as of 14:55, 7 September 2016
The following 2D interpolation methods are supported by GMS:
- Linear – Uses data points that are first triangulated to form a network of triangles.
- Inverse Distance Weighted – Based on the assumption that the interpolating surface should be influenced most by the nearby points and less by the more distant points.
- Clough-Tocher – A finite element method because it has origins in the finite element method of numerical analysis.
- Natural Neighbor – Based on the Thiessen polygon network of the point data.
- Kriging – Based on the assumption that the parameter being interpolated can be treated as a regionalized variable.
Log interpolation is also supported.
