Template:GMS 2D Interpolation Method: Difference between revisions
From XMS Wiki
Jump to navigationJump to search
No edit summary |
No edit summary |
||
| (6 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
The following 2D [[GMS:Interpolation|interpolation methods]] are supported by GMS: | The following 2D [[GMS:Interpolation|interpolation methods]] are supported by GMS: | ||
*[[GMS:Linear|Linear]] | *[[GMS:Linear|Linear]] – Uses data points that are first triangulated to form a network of triangles. | ||
*[[GMS:Inverse Distance Weighted|Inverse Distance Weighted]] | *[[GMS:Inverse Distance Weighted|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. | ||
*[[GMS:Clough-Tocher|Clough-Tocher]] | *[[GMS:Clough-Tocher|Clough-Tocher]] – A finite element method because it has origins in the finite element method of numerical analysis. | ||
*[[GMS:Natural Neighbor|Natural Neighbor]] | *[[GMS:Natural Neighbor|Natural Neighbor]] – Based on the Thiessen polygon network of the point data. | ||
*[[GMS:Kriging|Kriging]] | *[[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. | [[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.
