Pitney Bowes MapXtreme - Manual (Page 321)

Chapter 17: Working with Rasters and Grids
Grid Interpolators
MapXtreme v7.1 328 Developer Guide
The interpolators, IDW and TIN, provide algorithms for determining grid cell values according to their
particular formulas. IDW is best used for population data, while TIN is used for terrain data. See
Inverse Distance Weighted (IDW) Interpolator and Triangulated Irregular Network (TIN)
Interpolator .
If one of the provided interpolators does not meet your needs, you can create your own by deriving it
from the new IInterpolator interface. See
IInterpolator Interface and the
MapInfo.Raster.Interpolators namespace in the Developer Reference.
If your data includes coincident (duplicate) data points in the same cell location, the grid API
provides an aggregator class to sum or average the points. Other available aggregator methods are
count, min and max. You can also create or use any aggregator that implements
IGridCellAggregator.
Other enhancements to the Grid API include the ability to clip the grid to match the outline of the
map boundary. Grids are created based on the minimum bounding rectangle of the source data. If
you wish your grid boundary to follow the outline of your map boundary, you would set the
GridCreatorFromFeatures.ClippingGeometry property to the Geometry you wish the grid cells to be
clipped against.
Once you have created a grid from your data points, you can modify characteristics such as hill
shading, styles and inflection points using the new Grid Style dialog and Workspace Manager. See
Grid Style for more information.
Grid Interpolators
MapXtreme provides two grid interpolators for creating a continuous grid: IDW and TIN. The IDW
and TIN interpolators are included in a separate namespace called MapInfo.Raster.Interpolators.
In addition, MapXtreme provides an interface for creating your own interpolator.
Inverse Distance Weighted (IDW) Interpolator
The MapInfo.Raster.Interpolators.InverseDistanceWeighted interpolator class is one of two grid
interpolators provided with MapXtreme. The IDW interpolator is best suited for data values such as
population, or any data that yields arbitrary values over the grid rather than be related to or
influenced by, neighboring values. This interpolation method also works well for sparse data.
The IDW interpolator calculates the values contained in the cells that cover the grid. Each data point
value that is included in the calculation is weighted by its distance from the center of the cell.
Because the interpolation is an inverse distance weighting calculation, the farther the point is from
the cell, the less influence its value will have on the resulting cell value.
In IDW, an exponent determines how much influence each point will have on the result. The higher
the exponent the greater the influence closer points will have on the cell value. Exponents can range
from one to 10.
You can also choose an aggregation method for the values of source data points that are in the
same grid cell. Choose from: average, count, sum, min, and max.