Pitney Bowes MapInfo Vertical Mapper - Manual (Page 42)

Natural Neighbour Interpolation
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Vertical Mapper 3.7
• The Smoothed, without overshoot option uses the slope-based solution discussed earlier.
This variation of the Natural Neighbour method makes use of the slope of all adjacent points to
calculate the area-weighted value of each grid node. Undershoot and overshoot are controlled
by assigning a slope value of zero (horizontal) to all local minimum and maximum point values.
• The Smoother, allowing overshoot option uses the same slope-based method but allows
overshooting and undershooting of local lows and highs, generating a much smoother surface.
The Pick Boundary Region from Map Window check box enables you to choose a new boundary
region as the outer hull of the point data.
The File name box enables you to enter a new file name.
The Extents button displays a summary of the geographic size and the z-value range of the original
point database, the density of the points, and the data value units.
Exploring the Natural Neighbour: Point Aggregation Dialog Box
When you choose the Advanced option in the Select Interpolation Method dialog box, you are given
access to a variety of controls in the natural neighbour interpolation method that you can use to
make subtle adjustments to the grid surface generated from a MapInfo points table.
The Aggregation Type section contains the three major aggregation techniques supported by
Vertical Mapper. For more information about the operation and optimum usage of the forward
stepping, cluster density, and square cell techniques, see
Techniques for Data Aggregation on
page 174 .
The Aggregated Value section enables you to choose how the new aggregated value is calculated.
You can choose to average the aggregated values, average the minimum and maximum values,
sum the values, or assign the minimum, the maximum, the median, or the expected value to the new
aggregated point.
The Aggregation Distance box enables you to define the distance used to group points for
aggregation. This distance has a different meaning for each of the three methods. For the cluster
density and forward stepping methods, aggregation distance is defined by the radius of a user-
defined circular search area centred on each aggregation cell. For the square cell method,
aggregation distance is defined by the width of a square aggregation cell.